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.gitattributes

@@ -58,3 +58,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+classification/openml_ctr23/fps_benchmark/train.jsonl filter=lfs diff=lfs merge=lfs -text
+retrieval/queries.jsonl filter=lfs diff=lfs merge=lfs -text
+classification/openml_ctr23/superconductivity/train.jsonl filter=lfs diff=lfs merge=lfs -text
+classification/openml_cc18/har/train.jsonl filter=lfs diff=lfs merge=lfs -text
+classification/openml_cc18/isolet/train.jsonl filter=lfs diff=lfs merge=lfs -text
+classification/openml_cc18/madelon/train.jsonl filter=lfs diff=lfs merge=lfs -text

classification/grinsztajn/cat_clf/road-safety/test.csv

@@ -0,0 +1,1001 @@
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classification/openml_cc18/GesturePhaseSegmentationProcessed/metadata.json

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+{
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+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
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+}

classification/openml_cc18/MiceProtein/metadata.json

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+{
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+  "sub_benchmark": "",
+  "task_type": "clf",
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+  }
+}

classification/openml_cc18/MiceProtein/test.csv

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classification/openml_cc18/PhishingWebsites/metadata.json

@@ -0,0 +1,23 @@
+{
+  "dataset": "PhishingWebsites",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Result",
+  "label_values": [
+    "-1",
+    "1"
+  ],
+  "num_labels": 2,
+  "train_samples": 9000,
+  "test_samples": 1000,
+  "train_label_distribution": {
+    "-1": 3978,
+    "1": 5022
+  },
+  "test_label_distribution": {
+    "1": 558,
+    "-1": 442
+  }
+}

classification/openml_cc18/PhishingWebsites/test.csv

@@ -0,0 +1,1001 @@
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classification/openml_cc18/adult/metadata.json

@@ -0,0 +1,23 @@
+{
+  "dataset": "adult",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "class",
+  "label_values": [
+    ">50K",
+    "<=50K"
+  ],
+  "num_labels": 2,
+  "train_samples": 8999,
+  "test_samples": 1001,
+  "train_label_distribution": {
+    ">50K": 2107,
+    "<=50K": 6892
+  },
+  "test_label_distribution": {
+    "<=50K": 766,
+    ">50K": 235
+  }
+}

classification/openml_cc18/analcatdata_authorship/metadata.json

@@ -0,0 +1,29 @@
+{
+  "dataset": "analcatdata_authorship",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Author",
+  "label_values": [
+    "London",
+    "Milton",
+    "Shakespeare",
+    "Austen"
+  ],
+  "num_labels": 4,
+  "train_samples": 755,
+  "test_samples": 86,
+  "train_label_distribution": {
+    "Shakespeare": 155,
+    "Austen": 285,
+    "London": 266,
+    "Milton": 49
+  },
+  "test_label_distribution": {
+    "Shakespeare": 18,
+    "Austen": 32,
+    "Milton": 6,
+    "London": 30
+  }
+}

classification/openml_cc18/analcatdata_authorship/test.csv

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+30,6,0,4,67,2,2,17,7,9,8,12,8,1,8,0,3,2,16,6,24,2,11,29,17,4,29,1,6,18,1,1,3,5,0,10,24,4,48,5,4,5,15,0,0,6,5,7,3,15,58,15,1,5,1,5,58,0,1,38,14,2,5,10,1,6,18,4,0,6,Austen
+25,10,2,4,66,6,1,15,8,17,27,12,8,4,1,0,0,2,19,7,40,3,19,12,38,0,36,4,1,21,3,0,4,7,1,6,12,3,51,12,0,4,5,1,0,12,2,10,7,28,56,15,3,4,0,5,66,3,0,40,4,8,2,9,4,2,12,5,1,6,Austen
+40,6,0,4,58,8,4,18,10,10,5,16,6,1,4,1,1,5,11,4,14,3,12,11,21,6,20,2,13,27,1,0,6,6,13,5,23,4,52,11,6,3,8,4,4,3,4,3,4,20,56,2,2,5,1,2,39,5,3,26,11,6,4,1,4,1,17,5,7,4,Austen
+36,14,0,26,38,2,4,6,10,4,0,15,8,2,10,3,0,0,7,3,4,2,2,18,10,6,18,1,8,6,1,0,4,0,7,6,5,3,54,19,7,2,2,0,0,2,3,2,1,22,79,4,4,3,2,3,29,4,0,14,10,7,4,1,1,0,16,2,5,5,London
+33,14,2,4,89,4,1,16,9,4,5,8,3,1,1,1,0,0,9,6,10,1,6,4,22,3,33,5,6,10,1,0,4,2,7,3,6,1,72,4,5,1,3,0,0,5,0,3,4,33,116,8,3,5,1,7,40,5,0,32,17,2,4,2,6,5,10,2,3,1,London
+35,4,0,4,41,4,1,15,17,18,5,18,12,1,5,1,1,2,16,5,15,1,14,36,19,3,26,3,2,20,2,0,4,2,8,10,29,3,42,6,6,6,3,1,2,5,3,8,5,17,70,4,3,5,0,4,53,2,3,41,12,4,5,6,5,0,13,6,4,1,Austen
+39,5,1,1,93,0,4,11,11,2,4,12,7,0,0,5,0,1,11,7,8,1,6,6,20,0,29,3,4,10,0,0,2,1,23,8,7,3,65,13,1,1,4,1,2,6,0,1,5,16,114,5,1,5,1,3,33,2,4,41,12,2,9,2,4,1,21,3,0,2,London
+47,7,0,4,51,0,11,12,6,10,0,17,5,4,6,5,0,1,14,2,1,0,11,0,10,10,29,2,20,25,0,5,3,2,28,3,24,0,52,2,2,2,5,13,7,10,2,1,3,14,82,0,5,3,0,12,39,3,5,5,5,6,3,3,1,9,19,7,24,3,Shakespeare
+33,6,0,5,44,4,9,17,14,15,4,16,8,1,11,3,0,5,18,3,11,1,4,29,4,7,20,4,16,49,2,6,5,4,10,8,24,5,25,12,2,6,3,2,6,12,3,3,3,14,57,2,4,8,1,6,51,9,2,20,5,4,3,3,2,11,10,11,3,1,Austen
+33,4,0,1,55,4,4,13,16,21,6,17,12,5,1,2,1,2,19,7,12,3,10,51,28,1,35,3,7,18,2,5,2,2,2,4,22,4,51,5,3,6,5,0,0,14,4,5,0,17,78,9,3,2,0,6,53,0,4,34,7,5,5,7,0,7,16,9,8,1,Austen
+33,16,0,18,36,4,3,12,5,10,7,11,2,2,1,0,0,5,14,3,20,0,2,10,11,5,29,1,5,30,0,0,6,4,0,3,7,5,26,14,5,2,3,7,0,1,2,0,2,24,85,6,4,7,0,4,46,7,0,31,8,15,5,0,2,1,13,7,0,5,London
+30,10,0,3,61,11,0,18,20,14,4,9,11,0,4,0,0,4,24,16,11,4,11,46,8,2,34,1,5,13,4,4,1,1,2,14,12,4,56,7,4,4,8,0,2,4,4,5,2,17,68,5,3,7,1,2,62,1,2,37,19,2,7,9,1,8,15,3,5,6,Austen
+19,10,0,1,47,0,9,21,5,11,1,13,3,1,1,3,3,0,13,6,4,1,18,1,19,4,13,2,15,12,0,1,6,5,15,10,16,6,25,8,2,0,1,16,3,10,1,1,2,19,64,6,2,2,1,14,38,1,3,5,1,10,5,7,1,4,14,5,2,8,Shakespeare
+21,13,1,4,69,4,25,12,4,14,0,10,13,1,5,1,4,2,6,9,0,5,6,0,1,4,32,3,35,23,6,0,4,0,2,2,8,2,80,1,4,5,7,6,0,2,0,2,5,30,169,4,7,9,0,10,22,1,1,1,1,3,2,6,3,23,13,0,14,1,London
+30,8,0,32,52,1,3,6,6,6,3,11,11,0,1,2,1,3,15,6,21,0,4,17,20,1,21,0,1,14,1,1,2,2,1,11,10,1,38,17,5,1,6,1,2,8,0,1,1,12,117,11,2,7,2,4,29,7,1,39,7,1,9,0,4,0,9,2,1,4,London
+41,10,1,4,93,2,2,4,11,5,5,9,3,0,1,2,0,0,11,3,8,0,5,0,8,3,38,6,9,15,1,0,3,4,36,6,8,2,83,12,1,0,3,1,2,8,0,1,3,20,122,5,1,7,1,6,38,1,5,35,9,5,7,3,2,1,14,2,1,2,London
+38,3,0,7,80,0,0,8,12,2,3,9,9,0,0,4,2,1,12,8,21,0,3,0,33,0,30,6,1,21,2,0,0,0,1,8,8,1,49,11,3,7,5,0,0,1,2,1,0,10,129,14,2,4,0,4,40,0,8,39,15,2,7,7,3,0,17,2,0,3,London
+26,10,3,4,54,0,6,3,11,5,8,13,2,3,5,2,0,0,20,9,18,3,12,0,20,2,34,3,13,34,0,0,3,2,12,12,14,2,46,4,5,6,7,1,0,10,3,1,0,24,115,5,3,10,0,4,40,2,1,33,13,3,4,1,8,3,5,4,0,1,London
+30,20,0,9,57,2,0,14,8,20,9,5,15,0,1,0,1,3,9,11,20,1,7,27,10,1,28,4,1,16,5,1,6,4,2,5,12,1,78,8,1,2,6,1,3,7,6,4,5,22,113,7,0,3,0,5,40,2,1,35,13,9,8,14,1,0,16,4,1,1,Austen
+30,8,0,2,61,0,1,11,6,9,2,17,2,1,16,1,2,2,12,7,3,0,11,4,15,3,31,3,19,15,0,1,7,7,10,10,17,3,29,15,5,1,5,4,1,8,3,3,0,18,62,3,1,4,0,25,46,2,3,5,0,13,4,2,4,12,15,8,19,10,Shakespeare
+9,16,0,0,64,0,0,15,7,7,0,7,10,2,0,3,1,1,12,24,2,0,2,13,31,0,25,2,2,1,0,5,8,1,0,7,10,4,33,16,1,2,17,7,0,6,2,5,6,11,69,5,4,0,0,9,58,1,0,3,0,11,4,2,1,9,33,0,1,1,Milton
+39,18,1,24,44,4,3,6,6,7,3,17,3,2,6,4,1,1,6,10,9,3,2,14,4,4,19,3,7,30,2,0,3,0,5,5,6,5,34,20,5,0,5,3,0,5,2,0,1,16,100,5,7,8,0,5,39,11,2,30,13,9,6,3,1,0,8,2,3,5,London
+33,16,0,0,62,1,7,14,6,6,7,9,5,4,7,10,1,2,18,5,11,1,7,1,9,5,26,4,16,30,2,2,2,0,4,14,10,4,45,13,3,1,5,1,2,4,0,0,2,22,110,1,2,5,4,7,25,4,0,28,9,6,0,2,1,1,8,2,12,4,London
+33,9,0,17,46,4,0,14,7,4,2,12,7,3,2,3,4,1,13,5,16,2,4,13,40,12,28,1,1,35,3,0,4,0,2,12,12,2,39,12,3,8,2,1,0,1,3,8,4,18,76,3,3,6,0,9,41,5,0,46,8,5,8,0,2,0,11,9,0,5,London
+41,10,0,27,45,0,3,4,13,8,3,8,5,3,0,4,0,0,18,4,9,1,0,11,23,2,29,3,5,19,0,0,2,0,8,4,7,6,33,13,7,8,2,0,0,9,2,1,1,11,86,6,2,5,1,5,35,10,0,27,6,7,11,1,4,0,17,0,7,5,London
+37,4,0,6,60,3,10,7,6,13,3,7,6,2,13,2,1,1,14,5,1,0,14,7,17,7,23,1,24,13,0,4,4,2,17,6,13,9,33,7,5,1,5,4,7,11,4,4,2,20,55,2,2,1,1,9,37,5,7,3,1,11,4,0,3,9,14,2,16,3,Shakespeare
+8,18,0,1,64,1,4,11,8,7,1,16,9,4,0,5,0,0,13,17,7,0,2,5,46,1,26,0,8,3,0,2,3,2,5,8,8,9,26,8,3,3,7,1,1,11,3,3,4,26,51,5,8,2,1,9,49,1,1,6,0,14,2,14,4,5,21,5,0,1,Milton
+41,9,1,5,46,1,9,13,3,18,0,13,7,4,8,0,2,6,14,2,0,0,7,0,33,13,20,0,28,23,0,5,3,1,11,10,19,6,49,1,0,0,4,4,11,16,8,2,6,19,81,9,6,5,0,4,36,2,9,3,7,5,8,2,2,6,12,7,7,4,Shakespeare
+21,12,0,0,55,4,3,26,12,17,11,17,6,2,3,0,2,9,20,8,19,3,8,42,13,6,24,1,7,24,1,2,4,4,16,8,24,4,38,11,1,4,3,1,6,3,3,5,5,29,41,3,0,6,0,9,55,1,0,34,9,6,6,2,0,6,12,11,2,7,Austen
+31,13,0,8,64,2,6,12,9,13,3,14,9,0,11,2,3,5,11,8,4,0,8,0,15,5,33,0,15,8,0,2,5,1,28,8,14,6,53,9,0,0,4,6,2,13,4,5,3,22,54,5,4,2,1,18,35,6,1,5,2,4,5,9,1,7,14,7,5,2,Shakespeare
+15,6,0,9,46,3,3,13,8,8,2,12,13,2,9,4,0,0,8,11,0,0,4,0,19,8,13,1,15,8,0,2,4,2,16,6,14,1,47,4,4,1,10,10,2,10,0,1,0,8,63,11,2,1,0,9,51,3,1,3,3,7,2,5,4,10,20,2,13,12,Shakespeare
+29,4,0,8,39,3,1,13,12,29,8,7,15,2,0,2,3,5,17,8,15,0,9,47,10,5,37,3,0,18,4,1,5,8,3,3,14,0,69,5,0,4,8,0,6,7,7,3,2,20,113,3,1,2,1,6,61,4,4,28,8,3,4,20,3,1,12,6,0,1,Austen
+21,11,1,4,57,3,2,18,12,16,3,15,0,3,7,2,4,2,20,9,22,1,8,41,24,2,27,0,6,30,2,2,3,5,7,10,19,5,41,6,2,5,8,0,0,8,3,3,5,21,48,5,0,8,2,5,77,4,2,44,7,14,7,6,1,1,14,19,2,6,Austen
+28,8,0,6,48,4,10,19,2,14,5,21,4,4,4,0,2,3,14,4,15,6,21,45,16,4,33,1,17,20,1,1,13,6,16,9,21,7,47,9,2,4,5,0,3,7,3,7,7,14,54,1,3,5,0,10,49,2,1,21,6,13,5,3,4,12,12,7,17,6,Austen
+15,12,0,1,60,0,1,16,6,7,0,11,10,4,5,3,1,0,9,14,2,0,3,6,19,1,15,3,9,11,0,4,5,3,9,9,11,7,39,11,8,3,4,6,3,13,3,4,3,21,36,11,5,4,1,11,50,1,1,4,2,12,6,3,9,4,30,1,7,1,Milton
+34,8,1,4,81,0,0,6,10,5,8,13,4,0,0,9,3,2,8,6,28,1,9,19,42,0,25,2,11,27,1,0,3,0,4,4,16,1,51,10,4,3,6,0,0,4,0,1,2,14,134,5,7,7,6,4,35,6,5,44,10,2,2,2,4,0,12,5,0,6,London
+26,2,0,9,48,0,13,8,6,7,5,13,4,6,9,2,1,3,7,2,17,5,16,0,24,1,29,5,13,24,1,0,0,0,10,5,22,1,51,10,1,1,6,0,3,7,1,0,2,42,88,6,3,8,2,5,31,4,0,23,7,5,10,2,2,8,17,7,18,1,London
+25,10,0,3,51,6,6,21,6,33,7,10,8,4,6,3,0,2,19,4,21,10,11,35,20,7,20,2,18,20,2,4,2,9,16,6,10,5,36,8,6,3,2,3,7,11,3,6,2,19,40,11,5,2,3,9,59,1,0,18,3,8,3,1,1,14,11,12,3,7,Austen
+20,11,0,5,52,0,6,13,2,15,1,14,9,2,4,0,1,1,21,8,0,0,11,7,18,6,25,0,19,17,0,3,3,7,21,6,16,4,26,6,0,1,3,7,3,7,4,1,2,16,48,3,2,1,0,12,38,2,0,3,2,10,4,2,1,17,13,4,20,10,Shakespeare
+41,9,0,15,56,0,1,10,12,3,1,14,5,1,4,6,3,0,12,5,7,4,0,16,22,4,26,2,8,33,1,0,5,3,6,7,5,2,42,14,5,1,1,2,0,3,0,0,2,27,88,2,1,5,3,2,45,8,0,19,4,4,3,1,2,0,14,2,3,5,London
+15,12,0,1,79,2,5,9,10,14,9,5,10,1,0,0,0,1,23,7,13,5,6,0,6,0,34,3,11,13,6,1,0,0,1,7,10,2,85,6,3,0,12,9,0,3,0,2,4,15,169,8,1,3,2,8,35,2,2,24,32,1,6,2,5,8,12,5,0,1,London
+19,10,0,6,74,2,8,10,8,7,1,8,4,3,9,0,2,1,10,2,0,0,14,7,7,5,18,2,23,14,0,2,2,3,17,4,13,2,34,5,4,0,8,16,4,8,4,3,0,17,37,3,3,8,0,13,39,2,2,1,0,3,3,6,0,22,18,2,25,4,Shakespeare
+40,5,1,8,53,3,5,11,10,16,10,17,15,2,4,0,0,7,8,4,24,0,2,17,35,5,30,2,14,21,1,1,8,0,3,7,25,2,44,5,5,2,3,1,2,5,0,5,6,16,49,6,0,6,0,1,64,1,1,27,13,6,4,3,3,0,20,4,1,7,Austen
+49,7,0,8,45,3,5,12,7,6,2,11,4,5,10,1,0,0,7,1,6,5,9,8,24,8,9,1,30,9,0,4,5,3,3,11,30,4,16,6,6,0,3,0,3,16,1,4,8,20,29,1,5,6,0,6,22,4,2,13,7,9,4,1,4,7,3,6,3,6,Shakespeare
+39,6,0,42,34,1,0,3,10,6,2,9,2,2,4,3,0,2,10,5,6,1,4,6,9,8,29,1,8,27,1,0,1,0,15,6,4,3,35,11,1,1,2,2,1,4,2,3,0,21,104,5,3,2,6,1,32,6,1,14,0,5,4,0,2,0,17,1,9,5,London
+34,4,2,6,76,2,0,11,19,7,4,13,4,2,0,0,1,0,17,9,14,0,4,8,41,0,43,4,7,24,0,0,3,3,0,6,11,2,49,8,8,3,3,0,2,3,1,3,4,21,119,2,1,1,1,4,37,2,3,40,2,0,5,3,4,0,7,3,0,4,London
+26,9,0,0,43,0,11,15,3,14,1,8,10,2,1,2,1,0,17,10,6,0,12,8,9,3,17,1,13,15,0,1,7,3,38,2,15,6,32,6,1,0,0,12,3,12,1,1,3,22,54,3,7,1,0,19,34,1,6,14,5,3,7,11,4,6,13,3,17,8,Shakespeare
+12,9,0,3,56,0,8,10,7,6,2,13,7,0,4,0,0,0,14,4,5,0,12,4,19,3,19,2,33,11,0,1,3,2,50,7,15,7,37,6,2,0,1,5,3,9,1,2,2,12,54,5,5,7,0,6,55,1,1,4,1,10,2,9,6,13,20,3,15,1,Shakespeare
+46,12,0,3,66,9,4,16,13,13,4,8,8,1,0,1,5,0,21,12,16,3,6,62,3,3,30,3,9,14,1,2,6,5,0,10,16,2,54,7,8,1,7,0,4,7,1,3,3,17,67,6,2,5,1,4,47,2,3,40,11,7,5,6,8,4,9,1,0,1,Austen
+31,7,0,12,58,1,14,6,1,11,3,13,8,2,6,3,2,1,15,3,0,0,11,0,11,3,22,2,15,8,0,1,2,9,28,8,25,8,37,3,3,0,5,7,1,14,5,3,4,13,46,4,3,3,1,15,27,0,4,1,2,15,5,1,0,9,15,2,6,2,Shakespeare
+28,10,0,0,53,2,15,6,4,12,6,11,5,6,8,0,4,3,8,4,2,8,9,0,4,3,30,9,29,29,2,1,7,0,0,7,24,7,44,9,4,2,7,9,0,5,1,2,7,26,106,4,6,6,2,5,36,3,3,14,7,4,13,2,1,15,8,14,17,1,London
+27,8,0,2,75,4,8,8,2,11,3,15,6,0,9,0,0,0,11,2,5,0,13,1,6,6,15,2,25,19,0,3,1,0,30,5,12,8,51,3,1,1,5,13,5,6,4,1,4,12,61,4,6,2,0,10,28,4,0,2,1,5,3,12,1,10,11,3,17,3,Shakespeare
+21,7,1,8,49,2,2,20,11,20,9,20,7,1,6,1,1,3,16,4,18,2,18,32,11,10,36,0,4,20,1,3,4,7,6,12,17,0,46,8,2,7,3,0,1,12,4,4,3,16,59,3,1,8,1,5,65,4,0,30,4,7,3,6,5,10,11,14,7,6,Austen
+41,6,0,4,57,1,1,11,4,6,8,6,3,0,5,2,3,1,13,6,20,1,2,33,12,8,35,4,4,16,3,1,3,2,0,6,12,5,48,13,7,7,1,0,0,3,4,2,1,15,92,5,5,9,3,3,28,3,1,49,4,5,6,1,7,0,11,9,2,5,London
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classification/openml_cc18/analcatdata_authorship/test.jsonl

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+{"text": "The a is 30. The all is 6. The also is 0. The an is 4. The and is 67. The any is 2. The are is 2. The as is 17. The at is 7. The be is 9. The been is 8. The but is 12. The by is 8. The can is 1. The do is 8. The down is 0. The even is 3. The every is 2. The for is 16. The from is 6. The had is 24. The has is 2. The have is 11. The her is 29. The his is 17. The if is 4. The in is 29. The into is 1. The is is 6. The it is 18. The its is 1. The may is 1. The more is 3. The must is 5. The my is 0. The no is 10. The not is 24. The now is 4. The of is 48. The on is 5. The one is 4. The only is 5. The or is 15. The our is 0. The should is 0. The so is 6. The some is 5. The such is 7. The than is 3. The that is 15. The the is 58. The their is 15. The then is 1. The there is 5. The things is 1. The this is 5. The to is 58. The up is 0. The upon is 1. The was is 38. The were is 14. The what is 2. The when is 5. The which is 10. The who is 1. The will is 6. The with is 18. The would is 4. The your is 0. The BookID is 6.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 40. The all is 6. The also is 0. The an is 4. The and is 58. The any is 8. The are is 4. The as is 18. The at is 10. The be is 10. The been is 5. The but is 16. The by is 6. The can is 1. The do is 4. The down is 1. The even is 1. The every is 5. The for is 11. The from is 4. The had is 14. The has is 3. The have is 12. The her is 11. The his is 21. The if is 6. The in is 20. The into is 2. The is is 13. The it is 27. The its is 1. The may is 0. The more is 6. The must is 6. The my is 13. The no is 5. The not is 23. The now is 4. The of is 52. The on is 11. The one is 6. The only is 3. The or is 8. The our is 4. The should is 4. The so is 3. The some is 4. The such is 3. The than is 4. The that is 20. The the is 56. The their is 2. The then is 2. The there is 5. The things is 1. The this is 2. The to is 39. The up is 5. The upon is 3. The was is 26. The were is 11. The what is 6. The when is 4. The which is 1. The who is 4. The will is 1. The with is 17. The would is 5. The your is 7. The BookID is 4.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 33. The all is 14. The also is 2. The an is 4. The and is 89. The any is 4. The are is 1. The as is 16. The at is 9. The be is 4. The been is 5. The but is 8. The by is 3. The can is 1. The do is 1. The down is 1. The even is 0. The every is 0. The for is 9. The from is 6. The had is 10. The has is 1. The have is 6. The her is 4. The his is 22. The if is 3. The in is 33. The into is 5. The is is 6. The it is 10. The its is 1. The may is 0. The more is 4. The must is 2. The my is 7. The no is 3. The not is 6. The now is 1. The of is 72. The on is 4. The one is 5. The only is 1. The or is 3. The our is 0. The should is 0. The so is 5. The some is 0. The such is 3. The than is 4. The that is 33. The the is 116. The their is 8. The then is 3. The there is 5. The things is 1. The this is 7. The to is 40. The up is 5. The upon is 0. The was is 32. The were is 17. The what is 2. The when is 4. The which is 2. The who is 6. The will is 5. The with is 10. The would is 2. The your is 3. The BookID is 1.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 35. The all is 4. The also is 0. The an is 4. The and is 41. The any is 4. The are is 1. The as is 15. The at is 17. The be is 18. The been is 5. The but is 18. The by is 12. The can is 1. The do is 5. The down is 1. The even is 1. The every is 2. The for is 16. The from is 5. The had is 15. The has is 1. The have is 14. The her is 36. The his is 19. The if is 3. The in is 26. The into is 3. The is is 2. The it is 20. The its is 2. The may is 0. The more is 4. The must is 2. The my is 8. The no is 10. The not is 29. The now is 3. The of is 42. The on is 6. The one is 6. The only is 6. The or is 3. The our is 1. The should is 2. The so is 5. The some is 3. The such is 8. The than is 5. The that is 17. The the is 70. The their is 4. The then is 3. The there is 5. The things is 0. The this is 4. The to is 53. The up is 2. The upon is 3. The was is 41. The were is 12. The what is 4. The when is 5. The which is 6. The who is 5. The will is 0. The with is 13. The would is 6. The your is 4. The BookID is 1.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 39. The all is 5. The also is 1. The an is 1. The and is 93. The any is 0. The are is 4. The as is 11. The at is 11. The be is 2. The been is 4. The but is 12. The by is 7. The can is 0. The do is 0. The down is 5. The even is 0. The every is 1. The for is 11. The from is 7. The had is 8. The has is 1. The have is 6. The her is 6. The his is 20. The if is 0. The in is 29. The into is 3. The is is 4. The it is 10. The its is 0. The may is 0. The more is 2. The must is 1. The my is 23. The no is 8. The not is 7. The now is 3. The of is 65. The on is 13. The one is 1. The only is 1. The or is 4. The our is 1. The should is 2. The so is 6. The some is 0. The such is 1. The than is 5. The that is 16. The the is 114. The their is 5. The then is 1. The there is 5. The things is 1. The this is 3. The to is 33. The up is 2. The upon is 4. The was is 41. The were is 12. The what is 2. The when is 9. The which is 2. The who is 4. The will is 1. The with is 21. The would is 3. The your is 0. The BookID is 2.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 47. The all is 7. The also is 0. The an is 4. The and is 51. The any is 0. The are is 11. The as is 12. The at is 6. The be is 10. The been is 0. The but is 17. The by is 5. The can is 4. The do is 6. The down is 5. The even is 0. The every is 1. The for is 14. The from is 2. The had is 1. The has is 0. The have is 11. The her is 0. The his is 10. The if is 10. The in is 29. The into is 2. The is is 20. The it is 25. The its is 0. The may is 5. The more is 3. The must is 2. The my is 28. The no is 3. The not is 24. The now is 0. The of is 52. The on is 2. The one is 2. The only is 2. The or is 5. The our is 13. The should is 7. The so is 10. The some is 2. The such is 1. The than is 3. The that is 14. The the is 82. The their is 0. The then is 5. The there is 3. The things is 0. The this is 12. The to is 39. The up is 3. The upon is 5. The was is 5. The were is 5. The what is 6. The when is 3. The which is 3. The who is 1. The will is 9. The with is 19. The would is 7. The your is 24. The BookID is 3.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 33. The all is 6. The also is 0. The an is 5. The and is 44. The any is 4. The are is 9. The as is 17. The at is 14. The be is 15. The been is 4. The but is 16. The by is 8. The can is 1. The do is 11. The down is 3. The even is 0. The every is 5. The for is 18. The from is 3. The had is 11. The has is 1. The have is 4. The her is 29. The his is 4. The if is 7. The in is 20. The into is 4. The is is 16. The it is 49. The its is 2. The may is 6. The more is 5. The must is 4. The my is 10. The no is 8. The not is 24. The now is 5. The of is 25. The on is 12. The one is 2. The only is 6. The or is 3. The our is 2. The should is 6. The so is 12. The some is 3. The such is 3. The than is 3. The that is 14. The the is 57. The their is 2. The then is 4. The there is 8. The things is 1. The this is 6. The to is 51. The up is 9. The upon is 2. The was is 20. The were is 5. The what is 4. The when is 3. The which is 3. The who is 2. The will is 11. The with is 10. The would is 11. The your is 3. The BookID is 1.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 33. The all is 4. The also is 0. The an is 1. The and is 55. The any is 4. The are is 4. The as is 13. The at is 16. The be is 21. The been is 6. The but is 17. The by is 12. The can is 5. The do is 1. The down is 2. The even is 1. The every is 2. The for is 19. The from is 7. The had is 12. The has is 3. The have is 10. The her is 51. The his is 28. The if is 1. The in is 35. The into is 3. The is is 7. The it is 18. The its is 2. The may is 5. The more is 2. The must is 2. The my is 2. The no is 4. The not is 22. The now is 4. The of is 51. The on is 5. The one is 3. The only is 6. The or is 5. The our is 0. The should is 0. The so is 14. The some is 4. The such is 5. The than is 0. The that is 17. The the is 78. The their is 9. The then is 3. The there is 2. The things is 0. The this is 6. The to is 53. The up is 0. The upon is 4. The was is 34. The were is 7. The what is 5. The when is 5. The which is 7. The who is 0. The will is 7. The with is 16. The would is 9. The your is 8. The BookID is 1.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 33. The all is 16. The also is 0. The an is 18. The and is 36. The any is 4. The are is 3. The as is 12. The at is 5. The be is 10. The been is 7. The but is 11. The by is 2. The can is 2. The do is 1. The down is 0. The even is 0. The every is 5. The for is 14. The from is 3. The had is 20. The has is 0. The have is 2. The her is 10. The his is 11. The if is 5. The in is 29. The into is 1. The is is 5. The it is 30. The its is 0. The may is 0. The more is 6. The must is 4. The my is 0. The no is 3. The not is 7. The now is 5. The of is 26. The on is 14. The one is 5. The only is 2. The or is 3. The our is 7. The should is 0. The so is 1. The some is 2. The such is 0. The than is 2. The that is 24. The the is 85. The their is 6. The then is 4. The there is 7. The things is 0. The this is 4. The to is 46. The up is 7. The upon is 0. The was is 31. The were is 8. The what is 15. The when is 5. The which is 0. The who is 2. The will is 1. The with is 13. The would is 7. The your is 0. The BookID is 5.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 30. The all is 10. The also is 0. The an is 3. The and is 61. The any is 11. The are is 0. The as is 18. The at is 20. The be is 14. The been is 4. The but is 9. The by is 11. The can is 0. The do is 4. The down is 0. The even is 0. The every is 4. The for is 24. The from is 16. The had is 11. The has is 4. The have is 11. The her is 46. The his is 8. The if is 2. The in is 34. The into is 1. The is is 5. The it is 13. The its is 4. The may is 4. The more is 1. The must is 1. The my is 2. The no is 14. The not is 12. The now is 4. The of is 56. The on is 7. The one is 4. The only is 4. The or is 8. The our is 0. The should is 2. The so is 4. The some is 4. The such is 5. The than is 2. The that is 17. The the is 68. The their is 5. The then is 3. The there is 7. The things is 1. The this is 2. The to is 62. The up is 1. The upon is 2. The was is 37. The were is 19. The what is 2. The when is 7. The which is 9. The who is 1. The will is 8. The with is 15. The would is 3. The your is 5. The BookID is 6.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 19. The all is 10. The also is 0. The an is 1. The and is 47. The any is 0. The are is 9. The as is 21. The at is 5. The be is 11. The been is 1. The but is 13. The by is 3. The can is 1. The do is 1. The down is 3. The even is 3. The every is 0. The for is 13. The from is 6. The had is 4. The has is 1. The have is 18. The her is 1. The his is 19. The if is 4. The in is 13. The into is 2. The is is 15. The it is 12. The its is 0. The may is 1. The more is 6. The must is 5. The my is 15. The no is 10. The not is 16. The now is 6. The of is 25. The on is 8. The one is 2. The only is 0. The or is 1. The our is 16. The should is 3. The so is 10. The some is 1. The such is 1. The than is 2. The that is 19. The the is 64. The their is 6. The then is 2. The there is 2. The things is 1. The this is 14. The to is 38. The up is 1. The upon is 3. The was is 5. The were is 1. The what is 10. The when is 5. The which is 7. The who is 1. The will is 4. The with is 14. The would is 5. The your is 2. The BookID is 8.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 21. The all is 13. The also is 1. The an is 4. The and is 69. The any is 4. The are is 25. The as is 12. The at is 4. The be is 14. The been is 0. The but is 10. The by is 13. The can is 1. The do is 5. The down is 1. The even is 4. The every is 2. The for is 6. The from is 9. The had is 0. The has is 5. The have is 6. The her is 0. The his is 1. The if is 4. The in is 32. The into is 3. The is is 35. The it is 23. The its is 6. The may is 0. The more is 4. The must is 0. The my is 2. The no is 2. The not is 8. The now is 2. The of is 80. The on is 1. The one is 4. The only is 5. The or is 7. The our is 6. The should is 0. The so is 2. The some is 0. The such is 2. The than is 5. The that is 30. The the is 169. The their is 4. The then is 7. The there is 9. The things is 0. The this is 10. The to is 22. The up is 1. The upon is 1. The was is 1. The were is 1. The what is 3. The when is 2. The which is 6. The who is 3. The will is 23. The with is 13. The would is 0. The your is 14. The BookID is 1.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 30. The all is 8. The also is 0. The an is 32. The and is 52. The any is 1. The are is 3. The as is 6. The at is 6. The be is 6. The been is 3. The but is 11. The by is 11. The can is 0. The do is 1. The down is 2. The even is 1. The every is 3. The for is 15. The from is 6. The had is 21. The has is 0. The have is 4. The her is 17. The his is 20. The if is 1. The in is 21. The into is 0. The is is 1. The it is 14. The its is 1. The may is 1. The more is 2. The must is 2. The my is 1. The no is 11. The not is 10. The now is 1. The of is 38. The on is 17. The one is 5. The only is 1. The or is 6. The our is 1. The should is 2. The so is 8. The some is 0. The such is 1. The than is 1. The that is 12. The the is 117. The their is 11. The then is 2. The there is 7. The things is 2. The this is 4. The to is 29. The up is 7. The upon is 1. The was is 39. The were is 7. The what is 1. The when is 9. The which is 0. The who is 4. The will is 0. The with is 9. The would is 2. The your is 1. The BookID is 4.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 41. The all is 10. The also is 1. The an is 4. The and is 93. The any is 2. The are is 2. The as is 4. The at is 11. The be is 5. The been is 5. The but is 9. The by is 3. The can is 0. The do is 1. The down is 2. The even is 0. The every is 0. The for is 11. The from is 3. The had is 8. The has is 0. The have is 5. The her is 0. The his is 8. The if is 3. The in is 38. The into is 6. The is is 9. The it is 15. The its is 1. The may is 0. The more is 3. The must is 4. The my is 36. The no is 6. The not is 8. The now is 2. The of is 83. The on is 12. The one is 1. The only is 0. The or is 3. The our is 1. The should is 2. The so is 8. The some is 0. The such is 1. The than is 3. The that is 20. The the is 122. The their is 5. The then is 1. The there is 7. The things is 1. The this is 6. The to is 38. The up is 1. The upon is 5. The was is 35. The were is 9. The what is 5. The when is 7. The which is 3. The who is 2. The will is 1. The with is 14. The would is 2. The your is 1. The BookID is 2.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 26. The all is 10. The also is 3. The an is 4. The and is 54. The any is 0. The are is 6. The as is 3. The at is 11. The be is 5. The been is 8. The but is 13. The by is 2. The can is 3. The do is 5. The down is 2. The even is 0. The every is 0. The for is 20. The from is 9. The had is 18. The has is 3. The have is 12. The her is 0. The his is 20. The if is 2. The in is 34. The into is 3. The is is 13. The it is 34. The its is 0. The may is 0. The more is 3. The must is 2. The my is 12. The no is 12. The not is 14. The now is 2. The of is 46. The on is 4. The one is 5. The only is 6. The or is 7. The our is 1. The should is 0. The so is 10. The some is 3. The such is 1. The than is 0. The that is 24. The the is 115. The their is 5. The then is 3. The there is 10. The things is 0. The this is 4. The to is 40. The up is 2. The upon is 1. The was is 33. The were is 13. The what is 3. The when is 4. The which is 1. The who is 8. The will is 3. The with is 5. The would is 4. The your is 0. The BookID is 1.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 31. The all is 13. The also is 0. The an is 8. The and is 64. The any is 2. The are is 6. The as is 12. The at is 9. The be is 13. The been is 3. The but is 14. The by is 9. The can is 0. The do is 11. The down is 2. The even is 3. The every is 5. The for is 11. The from is 8. The had is 4. The has is 0. The have is 8. The her is 0. The his is 15. The if is 5. The in is 33. The into is 0. The is is 15. The it is 8. The its is 0. The may is 2. The more is 5. The must is 1. The my is 28. The no is 8. The not is 14. The now is 6. The of is 53. The on is 9. The one is 0. The only is 0. The or is 4. The our is 6. The should is 2. The so is 13. The some is 4. The such is 5. The than is 3. The that is 22. The the is 54. The their is 5. The then is 4. The there is 2. The things is 1. The this is 18. The to is 35. The up is 6. The upon is 1. The was is 5. The were is 2. The what is 4. The when is 5. The which is 9. The who is 1. The will is 7. The with is 14. The would is 7. The your is 5. The BookID is 2.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 15. The all is 6. The also is 0. The an is 9. The and is 46. The any is 3. The are is 3. The as is 13. The at is 8. The be is 8. The been is 2. The but is 12. The by is 13. The can is 2. The do is 9. The down is 4. The even is 0. The every is 0. The for is 8. The from is 11. The had is 0. The has is 0. The have is 4. The her is 0. The his is 19. The if is 8. The in is 13. The into is 1. The is is 15. The it is 8. The its is 0. The may is 2. The more is 4. The must is 2. The my is 16. The no is 6. The not is 14. The now is 1. The of is 47. The on is 4. The one is 4. The only is 1. The or is 10. The our is 10. The should is 2. The so is 10. The some is 0. The such is 1. The than is 0. The that is 8. The the is 63. The their is 11. The then is 2. The there is 1. The things is 0. The this is 9. The to is 51. The up is 3. The upon is 1. The was is 3. The were is 3. The what is 7. The when is 2. The which is 5. The who is 4. The will is 10. The with is 20. The would is 2. The your is 13. The BookID is 12.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 29. The all is 4. The also is 0. The an is 8. The and is 39. The any is 3. The are is 1. The as is 13. The at is 12. The be is 29. The been is 8. The but is 7. The by is 15. The can is 2. The do is 0. The down is 2. The even is 3. The every is 5. The for is 17. The from is 8. The had is 15. The has is 0. The have is 9. The her is 47. The his is 10. The if is 5. The in is 37. The into is 3. The is is 0. The it is 18. The its is 4. The may is 1. The more is 5. The must is 8. The my is 3. The no is 3. The not is 14. The now is 0. The of is 69. The on is 5. The one is 0. The only is 4. The or is 8. The our is 0. The should is 6. The so is 7. The some is 7. The such is 3. The than is 2. The that is 20. The the is 113. The their is 3. The then is 1. The there is 2. The things is 1. The this is 6. The to is 61. The up is 4. The upon is 4. The was is 28. The were is 8. The what is 3. The when is 4. The which is 20. The who is 3. The will is 1. The with is 12. The would is 6. The your is 0. The BookID is 1.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 21. The all is 11. The also is 1. The an is 4. The and is 57. The any is 3. The are is 2. The as is 18. The at is 12. The be is 16. The been is 3. The but is 15. The by is 0. The can is 3. The do is 7. The down is 2. The even is 4. The every is 2. The for is 20. The from is 9. The had is 22. The has is 1. The have is 8. The her is 41. The his is 24. The if is 2. The in is 27. The into is 0. The is is 6. The it is 30. The its is 2. The may is 2. The more is 3. The must is 5. The my is 7. The no is 10. The not is 19. The now is 5. The of is 41. The on is 6. The one is 2. The only is 5. The or is 8. The our is 0. The should is 0. The so is 8. The some is 3. The such is 3. The than is 5. The that is 21. The the is 48. The their is 5. The then is 0. The there is 8. The things is 2. The this is 5. The to is 77. The up is 4. The upon is 2. The was is 44. The were is 7. The what is 14. The when is 7. The which is 6. The who is 1. The will is 1. The with is 14. The would is 19. The your is 2. The BookID is 6.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 28. The all is 8. The also is 0. The an is 6. The and is 48. The any is 4. The are is 10. The as is 19. The at is 2. The be is 14. The been is 5. The but is 21. The by is 4. The can is 4. The do is 4. The down is 0. The even is 2. The every is 3. The for is 14. The from is 4. The had is 15. The has is 6. The have is 21. The her is 45. The his is 16. The if is 4. The in is 33. The into is 1. The is is 17. The it is 20. The its is 1. The may is 1. The more is 13. The must is 6. The my is 16. The no is 9. The not is 21. The now is 7. The of is 47. The on is 9. The one is 2. The only is 4. The or is 5. The our is 0. The should is 3. The so is 7. The some is 3. The such is 7. The than is 7. The that is 14. The the is 54. The their is 1. The then is 3. The there is 5. The things is 0. The this is 10. The to is 49. The up is 2. The upon is 1. The was is 21. The were is 6. The what is 13. The when is 5. The which is 3. The who is 4. The will is 12. The with is 12. The would is 7. The your is 17. The BookID is 6.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 34. The all is 8. The also is 1. The an is 4. The and is 81. The any is 0. The are is 0. The as is 6. The at is 10. The be is 5. The been is 8. The but is 13. The by is 4. The can is 0. The do is 0. The down is 9. The even is 3. The every is 2. The for is 8. The from is 6. The had is 28. The has is 1. The have is 9. The her is 19. The his is 42. The if is 0. The in is 25. The into is 2. The is is 11. The it is 27. The its is 1. The may is 0. The more is 3. The must is 0. The my is 4. The no is 4. The not is 16. The now is 1. The of is 51. The on is 10. The one is 4. The only is 3. The or is 6. The our is 0. The should is 0. The so is 4. The some is 0. The such is 1. The than is 2. The that is 14. The the is 134. The their is 5. The then is 7. The there is 7. The things is 6. The this is 4. The to is 35. The up is 6. The upon is 5. The was is 44. The were is 10. The what is 2. The when is 2. The which is 2. The who is 4. The will is 0. The with is 12. The would is 5. The your is 0. The BookID is 6.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 19. The all is 10. The also is 0. The an is 6. The and is 74. The any is 2. The are is 8. The as is 10. The at is 8. The be is 7. The been is 1. The but is 8. The by is 4. The can is 3. The do is 9. The down is 0. The even is 2. The every is 1. The for is 10. The from is 2. The had is 0. The has is 0. The have is 14. The her is 7. The his is 7. The if is 5. The in is 18. The into is 2. The is is 23. The it is 14. The its is 0. The may is 2. The more is 2. The must is 3. The my is 17. The no is 4. The not is 13. The now is 2. The of is 34. The on is 5. The one is 4. The only is 0. The or is 8. The our is 16. The should is 4. The so is 8. The some is 4. The such is 3. The than is 0. The that is 17. The the is 37. The their is 3. The then is 3. The there is 8. The things is 0. The this is 13. The to is 39. The up is 2. The upon is 2. The was is 1. The were is 0. The what is 3. The when is 3. The which is 6. The who is 0. The will is 22. The with is 18. The would is 2. The your is 25. The BookID is 4.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 26. The all is 9. The also is 0. The an is 0. The and is 43. The any is 0. The are is 11. The as is 15. The at is 3. The be is 14. The been is 1. The but is 8. The by is 10. The can is 2. The do is 1. The down is 2. The even is 1. The every is 0. The for is 17. The from is 10. The had is 6. The has is 0. The have is 12. The her is 8. The his is 9. The if is 3. The in is 17. The into is 1. The is is 13. The it is 15. The its is 0. The may is 1. The more is 7. The must is 3. The my is 38. The no is 2. The not is 15. The now is 6. The of is 32. The on is 6. The one is 1. The only is 0. The or is 0. The our is 12. The should is 3. The so is 12. The some is 1. The such is 1. The than is 3. The that is 22. The the is 54. The their is 3. The then is 7. The there is 1. The things is 0. The this is 19. The to is 34. The up is 1. The upon is 6. The was is 14. The were is 5. The what is 3. The when is 7. The which is 11. The who is 4. The will is 6. The with is 13. The would is 3. The your is 17. The BookID is 8.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 12. The all is 9. The also is 0. The an is 3. The and is 56. The any is 0. The are is 8. The as is 10. The at is 7. The be is 6. The been is 2. The but is 13. The by is 7. The can is 0. The do is 4. The down is 0. The even is 0. The every is 0. The for is 14. The from is 4. The had is 5. The has is 0. The have is 12. The her is 4. The his is 19. The if is 3. The in is 19. The into is 2. The is is 33. The it is 11. The its is 0. The may is 1. The more is 3. The must is 2. The my is 50. The no is 7. The not is 15. The now is 7. The of is 37. The on is 6. The one is 2. The only is 0. The or is 1. The our is 5. The should is 3. The so is 9. The some is 1. The such is 2. The than is 2. The that is 12. The the is 54. The their is 5. The then is 5. The there is 7. The things is 0. The this is 6. The to is 55. The up is 1. The upon is 1. The was is 4. The were is 1. The what is 10. The when is 2. The which is 9. The who is 6. The will is 13. The with is 20. The would is 3. The your is 15. The BookID is 1.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 46. The all is 12. The also is 0. The an is 3. The and is 66. The any is 9. The are is 4. The as is 16. The at is 13. The be is 13. The been is 4. The but is 8. The by is 8. The can is 1. The do is 0. The down is 1. The even is 5. The every is 0. The for is 21. The from is 12. The had is 16. The has is 3. The have is 6. The her is 62. The his is 3. The if is 3. The in is 30. The into is 3. The is is 9. The it is 14. The its is 1. The may is 2. The more is 6. The must is 5. The my is 0. The no is 10. The not is 16. The now is 2. The of is 54. The on is 7. The one is 8. The only is 1. The or is 7. The our is 0. The should is 4. The so is 7. The some is 1. The such is 3. The than is 3. The that is 17. The the is 67. The their is 6. The then is 2. The there is 5. The things is 1. The this is 4. The to is 47. The up is 2. The upon is 3. The was is 40. The were is 11. The what is 7. The when is 5. The which is 6. The who is 8. The will is 4. The with is 9. The would is 1. The your is 0. The BookID is 1.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 31. The all is 7. The also is 0. The an is 12. The and is 58. The any is 1. The are is 14. The as is 6. The at is 1. The be is 11. The been is 3. The but is 13. The by is 8. The can is 2. The do is 6. The down is 3. The even is 2. The every is 1. The for is 15. The from is 3. The had is 0. The has is 0. The have is 11. The her is 0. The his is 11. The if is 3. The in is 22. The into is 2. The is is 15. The it is 8. The its is 0. The may is 1. The more is 2. The must is 9. The my is 28. The no is 8. The not is 25. The now is 8. The of is 37. The on is 3. The one is 3. The only is 0. The or is 5. The our is 7. The should is 1. The so is 14. The some is 5. The such is 3. The than is 4. The that is 13. The the is 46. The their is 4. The then is 3. The there is 3. The things is 1. The this is 15. The to is 27. The up is 0. The upon is 4. The was is 1. The were is 2. The what is 15. The when is 5. The which is 1. The who is 0. The will is 9. The with is 15. The would is 2. The your is 6. The BookID is 2.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 28. The all is 10. The also is 0. The an is 0. The and is 53. The any is 2. The are is 15. The as is 6. The at is 4. The be is 12. The been is 6. The but is 11. The by is 5. The can is 6. The do is 8. The down is 0. The even is 4. The every is 3. The for is 8. The from is 4. The had is 2. The has is 8. The have is 9. The her is 0. The his is 4. The if is 3. The in is 30. The into is 9. The is is 29. The it is 29. The its is 2. The may is 1. The more is 7. The must is 0. The my is 0. The no is 7. The not is 24. The now is 7. The of is 44. The on is 9. The one is 4. The only is 2. The or is 7. The our is 9. The should is 0. The so is 5. The some is 1. The such is 2. The than is 7. The that is 26. The the is 106. The their is 4. The then is 6. The there is 6. The things is 2. The this is 5. The to is 36. The up is 3. The upon is 3. The was is 14. The were is 7. The what is 4. The when is 13. The which is 2. The who is 1. The will is 15. The with is 8. The would is 14. The your is 17. The BookID is 1.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 27. The all is 8. The also is 0. The an is 2. The and is 75. The any is 4. The are is 8. The as is 8. The at is 2. The be is 11. The been is 3. The but is 15. The by is 6. The can is 0. The do is 9. The down is 0. The even is 0. The every is 0. The for is 11. The from is 2. The had is 5. The has is 0. The have is 13. The her is 1. The his is 6. The if is 6. The in is 15. The into is 2. The is is 25. The it is 19. The its is 0. The may is 3. The more is 1. The must is 0. The my is 30. The no is 5. The not is 12. The now is 8. The of is 51. The on is 3. The one is 1. The only is 1. The or is 5. The our is 13. The should is 5. The so is 6. The some is 4. The such is 1. The than is 4. The that is 12. The the is 61. The their is 4. The then is 6. The there is 2. The things is 0. The this is 10. The to is 28. The up is 4. The upon is 0. The was is 2. The were is 1. The what is 5. The when is 3. The which is 12. The who is 1. The will is 10. The with is 11. The would is 3. The your is 17. The BookID is 3.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The a is 26. The all is 2. The also is 0. The an is 1. The and is 43. The any is 2. The are is 12. The as is 8. The at is 1. The be is 10. The been is 1. The but is 18. The by is 2. The can is 3. The do is 12. The down is 2. The even is 1. The every is 0. The for is 15. The from is 4. The had is 0. The has is 0. The have is 7. The her is 6. The his is 10. The if is 10. The in is 23. The into is 5. The is is 23. The it is 10. The its is 0. The may is 1. The more is 3. The must is 6. The my is 36. The no is 10. The not is 13. The now is 5. The of is 29. The on is 5. The one is 4. The only is 0. The or is 7. The our is 11. The should is 3. The so is 11. The some is 7. The such is 2. The than is 0. The that is 12. The the is 70. The their is 3. The then is 2. The there is 3. The things is 0. The this is 17. The to is 27. The up is 1. The upon is 5. The was is 1. The were is 1. The what is 15. The when is 4. The which is 1. The who is 3. The will is 3. The with is 17. The would is 6. The your is 17. The BookID is 10.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 20. The all is 9. The also is 2. The an is 2. The and is 58. The any is 1. The are is 6. The as is 17. The at is 8. The be is 6. The been is 3. The but is 9. The by is 5. The can is 2. The do is 3. The down is 1. The even is 0. The every is 0. The for is 14. The from is 8. The had is 1. The has is 0. The have is 6. The her is 7. The his is 15. The if is 2. The in is 42. The into is 8. The is is 11. The it is 6. The its is 0. The may is 2. The more is 4. The must is 2. The my is 8. The no is 4. The not is 7. The now is 2. The of is 60. The on is 4. The one is 9. The only is 3. The or is 6. The our is 17. The should is 2. The so is 7. The some is 5. The such is 2. The than is 3. The that is 17. The the is 100. The their is 13. The then is 6. The there is 3. The things is 1. The this is 10. The to is 40. The up is 2. The upon is 4. The was is 7. The were is 0. The what is 2. The when is 3. The which is 7. The who is 9. The will is 3. The with is 24. The would is 1. The your is 24. The BookID is 4.", "label": "Shakespeare", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 50. The all is 4. The also is 1. The an is 22. The and is 61. The any is 1. The are is 0. The as is 3. The at is 9. The be is 3. The been is 3. The but is 10. The by is 6. The can is 2. The do is 0. The down is 5. The even is 1. The every is 1. The for is 8. The from is 7. The had is 10. The has is 0. The have is 3. The her is 40. The his is 1. The if is 5. The in is 17. The into is 1. The is is 2. The it is 27. The its is 3. The may is 0. The more is 2. The must is 0. The my is 3. The no is 5. The not is 4. The now is 2. The of is 59. The on is 22. The one is 1. The only is 5. The or is 2. The our is 0. The should is 0. The so is 5. The some is 0. The such is 1. The than is 1. The that is 11. The the is 142. The their is 3. The then is 3. The there is 4. The things is 1. The this is 3. The to is 35. The up is 9. The upon is 1. The was is 21. The were is 7. The what is 5. The when is 0. The which is 2. The who is 0. The will is 0. The with is 27. The would is 0. The your is 0. The BookID is 5.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 38. The all is 6. The also is 0. The an is 3. The and is 74. The any is 1. The are is 0. The as is 7. The at is 2. The be is 6. The been is 2. The but is 13. The by is 11. The can is 0. The do is 3. The down is 1. The even is 1. The every is 1. The for is 16. The from is 6. The had is 13. The has is 0. The have is 7. The her is 0. The his is 12. The if is 1. The in is 27. The into is 2. The is is 2. The it is 20. The its is 1. The may is 0. The more is 7. The must is 2. The my is 13. The no is 8. The not is 19. The now is 2. The of is 65. The on is 8. The one is 8. The only is 2. The or is 2. The our is 10. The should is 3. The so is 10. The some is 1. The such is 2. The than is 5. The that is 25. The the is 116. The their is 2. The then is 3. The there is 5. The things is 1. The this is 4. The to is 47. The up is 2. The upon is 2. The was is 47. The were is 19. The what is 2. The when is 3. The which is 3. The who is 1. The will is 0. The with is 27. The would is 7. The your is 2. The BookID is 2.", "label": "London", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 30. The all is 13. The also is 2. The an is 4. The and is 61. The any is 5. The are is 4. The as is 24. The at is 17. The be is 18. The been is 3. The but is 16. The by is 8. The can is 4. The do is 10. The down is 0. The even is 1. The every is 4. The for is 16. The from is 10. The had is 12. The has is 0. The have is 11. The her is 32. The his is 16. The if is 6. The in is 28. The into is 2. The is is 13. The it is 22. The its is 0. The may is 3. The more is 8. The must is 4. The my is 7. The no is 3. The not is 17. The now is 2. The of is 48. The on is 9. The one is 4. The only is 2. The or is 5. The our is 0. The should is 2. The so is 7. The some is 2. The such is 2. The than is 4. The that is 17. The the is 74. The their is 4. The then is 2. The there is 9. The things is 1. The this is 5. The to is 51. The up is 3. The upon is 1. The was is 27. The were is 4. The what is 1. The when is 2. The which is 8. The who is 3. The will is 5. The with is 14. The would is 9. The your is 5. The BookID is 6.", "label": "Austen", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The a is 6. The all is 10. The also is 2. The an is 0. The and is 68. The any is 1. The are is 2. The as is 12. The at is 4. The be is 8. The been is 0. The but is 17. The by is 5. The can is 3. The do is 1. The down is 1. The even is 2. The every is 2. The for is 6. The from is 9. The had is 1. The has is 0. The have is 3. The her is 13. The his is 16. The if is 5. The in is 30. The into is 2. The is is 2. The it is 6. The its is 0. The may is 1. The more is 9. The must is 0. The my is 14. The no is 1. The not is 12. The now is 9. The of is 35. The on is 12. The one is 3. The only is 3. The or is 25. The our is 5. The should is 0. The so is 10. The some is 1. The such is 6. The than is 3. The that is 24. The the is 56. The their is 9. The then is 5. The there is 1. The things is 4. The this is 12. The to is 43. The up is 3. The upon is 0. The was is 5. The were is 1. The what is 7. The when is 7. The which is 7. The who is 5. The will is 2. The with is 24. The would is 0. The your is 5. The BookID is 1.", "label": "Milton", "dataset": "analcatdata_authorship", "benchmark": "openml_cc18", "task_type": "clf"}

classification/openml_cc18/analcatdata_dmft/metadata.json

@@ -0,0 +1,35 @@
+{
+  "dataset": "analcatdata_dmft",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Prevention",
+  "label_values": [
+    "Diet_enrichment",
+    "Mouthwash",
+    "nan",
+    "Oral_hygiene",
+    "All_methods",
+    "Health_education"
+  ],
+  "num_labels": 6,
+  "train_samples": 714,
+  "test_samples": 83,
+  "train_label_distribution": {
+    "Oral_hygiene": 110,
+    "Health_education": 111,
+    "Mouthwash": 139,
+    "All_methods": 114,
+    "nan": 122,
+    "Diet_enrichment": 118
+  },
+  "test_label_distribution": {
+    "Health_education": 13,
+    "nan": 14,
+    "Mouthwash": 16,
+    "Oral_hygiene": 13,
+    "All_methods": 13,
+    "Diet_enrichment": 14
+  }
+}

classification/openml_cc18/analcatdata_dmft/test.csv

@@ -0,0 +1,84 @@
+DMFT_Begin,DMFT_End,Gender,Ethnic,Prevention
+7,0,Male,White,Health_education
+7,3,Male,White,nan
+7,5,Female,White,Health_education
+5,0,Male,Dark,Mouthwash
+6,3,Female,White,nan
+1,0,Female,White,Oral_hygiene
+3,1,Male,Dark,Oral_hygiene
+4,4,Male,Dark,nan
+0,0,Male,Black,All_methods
+2,1,Male,White,Oral_hygiene
+0,2,Female,Black,Diet_enrichment
+5,1,Female,Dark,Health_education
+4,3,Female,Dark,Mouthwash
+0,1,Male,Black,Diet_enrichment
+2,2,Female,White,Health_education
+4,0,Female,White,Health_education
+0,0,Female,White,Health_education
+3,1,Female,Black,Oral_hygiene
+3,3,Female,White,Oral_hygiene
+4,0,Male,White,Health_education
+5,1,Female,White,All_methods
+4,4,Male,Dark,Health_education
+7,0,Male,Dark,Diet_enrichment
+2,0,Female,Dark,Diet_enrichment
+0,0,Male,Black,Mouthwash
+1,3,Male,White,Mouthwash
+4,0,Male,Dark,Health_education
+3,0,Male,White,nan
+2,2,Male,White,Oral_hygiene
+4,0,Female,White,nan
+8,4,Male,Dark,All_methods
+5,2,Female,Dark,All_methods
+5,1,Male,White,nan
+6,4,Male,White,Oral_hygiene
+0,0,Female,White,Health_education
+0,1,Male,Black,Diet_enrichment
+5,4,Female,White,nan
+0,0,Female,Black,nan
+3,0,Female,White,Diet_enrichment
+0,0,Male,Dark,Mouthwash
+2,1,Male,Dark,Mouthwash
+7,5,Male,White,Diet_enrichment
+4,5,Male,White,nan
+8,2,Male,Dark,Diet_enrichment
+8,4,Male,Dark,All_methods
+5,1,Male,Dark,All_methods
+0,0,Male,Dark,Mouthwash
+5,1,Female,White,Mouthwash
+0,0,Male,Black,nan
+1,2,Female,Black,Health_education
+3,3,Male,Dark,Health_education
+6,3,Female,White,Diet_enrichment
+1,0,Female,Black,All_methods
+0,0,Male,Dark,nan
+6,0,Male,Black,All_methods
+0,0,Male,White,Mouthwash
+0,1,Female,White,Oral_hygiene
+2,2,Male,Dark,All_methods
+5,4,Male,Dark,Mouthwash
+0,0,Male,White,Oral_hygiene
+5,5,Female,White,nan
+2,3,Female,Black,nan
+0,0,Male,Dark,Mouthwash
+0,1,Female,Dark,Diet_enrichment
+7,1,Female,White,Mouthwash
+0,1,Male,Dark,All_methods
+2,1,Male,White,Health_education
+4,0,Female,Dark,Oral_hygiene
+0,3,Female,White,Diet_enrichment
+3,1,Female,White,All_methods
+4,0,Male,Black,All_methods
+0,0,Female,White,Mouthwash
+6,3,Female,Dark,Mouthwash
+4,4,Female,White,Mouthwash
+8,3,Male,Dark,Diet_enrichment
+2,0,Male,White,Oral_hygiene
+2,0,Female,White,Mouthwash
+0,0,Female,White,nan
+7,4,Male,Dark,Diet_enrichment
+2,0,Female,White,Oral_hygiene
+3,2,Female,White,Oral_hygiene
+2,3,Female,White,Diet_enrichment
+7,5,Male,White,All_methods

classification/openml_cc18/analcatdata_dmft/test.jsonl

@@ -0,0 +1,83 @@
+{"text": "The DMFT_Begin is 7. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 3. The Gender is Male. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 5. The Gender is Female. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 6. The DMFT_End is 3. The Gender is Female. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 1. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 1. The Gender is Male. The Ethnic is Dark.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Black.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 1. The Gender is Male. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 2. The Gender is Female. The Ethnic is Black.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 1. The Gender is Female. The Ethnic is Dark.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 3. The Gender is Female. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 1. The Gender is Male. The Ethnic is Black.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 2. The Gender is Female. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 1. The Gender is Female. The Ethnic is Black.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 3. The Gender is Female. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 1. The Gender is Female. The Ethnic is White.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 0. The Gender is Female. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Black.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 1. The DMFT_End is 3. The Gender is Male. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 2. The Gender is Male. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 8. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 2. The Gender is Female. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 1. The Gender is Male. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 6. The DMFT_End is 4. The Gender is Male. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 1. The Gender is Male. The Ethnic is Black.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 4. The Gender is Female. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Female. The Ethnic is Black.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 1. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 5. The Gender is Male. The Ethnic is White.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 5. The Gender is Male. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 8. The DMFT_End is 2. The Gender is Male. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 8. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 1. The Gender is Male. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 1. The Gender is Female. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Black.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 1. The DMFT_End is 2. The Gender is Female. The Ethnic is Black.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 3. The Gender is Male. The Ethnic is Dark.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 6. The DMFT_End is 3. The Gender is Female. The Ethnic is White.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 1. The DMFT_End is 0. The Gender is Female. The Ethnic is Black.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 6. The DMFT_End is 0. The Gender is Male. The Ethnic is Black.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 1. The Gender is Female. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 2. The Gender is Male. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 5. The DMFT_End is 5. The Gender is Female. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 3. The Gender is Female. The Ethnic is Black.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Male. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 1. The Gender is Female. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 1. The Gender is Female. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 1. The Gender is Male. The Ethnic is Dark.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 1. The Gender is Male. The Ethnic is White.", "label": "Health_education", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Female. The Ethnic is Dark.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 3. The Gender is Female. The Ethnic is White.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 1. The Gender is Female. The Ethnic is White.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 0. The Gender is Male. The Ethnic is Black.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 6. The DMFT_End is 3. The Gender is Female. The Ethnic is Dark.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 4. The DMFT_End is 4. The Gender is Female. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 8. The DMFT_End is 3. The Gender is Male. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 0. The Gender is Male. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Mouthwash", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 0. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "nan", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 4. The Gender is Male. The Ethnic is Dark.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 0. The Gender is Female. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 3. The DMFT_End is 2. The Gender is Female. The Ethnic is White.", "label": "Oral_hygiene", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 2. The DMFT_End is 3. The Gender is Female. The Ethnic is White.", "label": "Diet_enrichment", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The DMFT_Begin is 7. The DMFT_End is 5. The Gender is Male. The Ethnic is White.", "label": "All_methods", "dataset": "analcatdata_dmft", "benchmark": "openml_cc18", "task_type": "clf"}

classification/openml_cc18/analcatdata_dmft/train.csv

@@ -0,0 +1,715 @@
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+7,1,Female,Dark,Mouthwash
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+5,3,Female,White,Diet_enrichment
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+6,3,Male,Dark,Diet_enrichment
+5,3,Male,Dark,nan
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+7,5,Male,Dark,Oral_hygiene
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+7,5,Male,White,nan
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+8,3,Male,Black,nan
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+6,5,Male,Dark,nan
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+5,3,Male,Dark,nan
+1,1,Male,Dark,Diet_enrichment
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classification/openml_cc18/balance-scale/metadata.json

@@ -0,0 +1,26 @@
+{
+  "dataset": "balance-scale",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "class",
+  "label_values": [
+    "R",
+    "B",
+    "L"
+  ],
+  "num_labels": 3,
+  "train_samples": 562,
+  "test_samples": 63,
+  "train_label_distribution": {
+    "L": 259,
+    "R": 259,
+    "B": 44
+  },
+  "test_label_distribution": {
+    "L": 29,
+    "B": 5,
+    "R": 29
+  }
+}

classification/openml_cc18/balance-scale/test.csv

@@ -0,0 +1,64 @@
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classification/openml_cc18/balance-scale/test.jsonl

@@ -0,0 +1,63 @@
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+{"text": "The left-weight is 2.0. The left-distance is 4.0. The right-weight is 4.0. The right-distance is 2.0.", "label": "B", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The left-weight is 5.0. The left-distance is 1.0. The right-weight is 1.0. The right-distance is 4.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 4.0. The left-distance is 4.0. The right-weight is 5.0. The right-distance is 1.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 2.0. The left-distance is 2.0. The right-weight is 1.0. The right-distance is 1.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 2.0. The left-distance is 5.0. The right-weight is 3.0. The right-distance is 2.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 1.0. The left-distance is 5.0. The right-weight is 5.0. The right-distance is 4.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 5.0. The left-distance is 4.0. The right-weight is 3.0. The right-distance is 3.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 3.0. The left-distance is 2.0. The right-weight is 5.0. The right-distance is 2.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 5.0. The left-distance is 1.0. The right-weight is 2.0. The right-distance is 2.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 1.0. The left-distance is 3.0. The right-weight is 4.0. The right-distance is 2.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 2.0. The left-distance is 1.0. The right-weight is 3.0. The right-distance is 3.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 5.0. The left-distance is 1.0. The right-weight is 4.0. The right-distance is 4.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 3.0. The left-distance is 5.0. The right-weight is 2.0. The right-distance is 3.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 2.0. The left-distance is 5.0. The right-weight is 3.0. The right-distance is 3.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 4.0. The left-distance is 3.0. The right-weight is 4.0. The right-distance is 1.0.", "label": "L", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 1.0. The left-distance is 3.0. The right-weight is 3.0. The right-distance is 4.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 2.0. The left-distance is 5.0. The right-weight is 5.0. The right-distance is 2.0.", "label": "B", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 1.0. The left-distance is 2.0. The right-weight is 3.0. The right-distance is 4.0.", "label": "R", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The left-weight is 3.0. The left-distance is 5.0. The right-weight is 5.0. The right-distance is 3.0.", "label": "B", "dataset": "balance-scale", "benchmark": "openml_cc18", "task_type": "clf"}

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classification/openml_cc18/bank-marketing/metadata.json

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+{
+  "dataset": "bank-marketing",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Class",
+  "label_values": [
+    "2",
+    "1"
+  ],
+  "num_labels": 2,
+  "train_samples": 8999,
+  "test_samples": 1001,
+  "train_label_distribution": {
+    "1": 7914,
+    "2": 1085
+  },
+  "test_label_distribution": {
+    "1": 880,
+    "2": 121
+  }
+}

classification/openml_cc18/bank-marketing/test.csv

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classification/openml_cc18/banknote-authentication/metadata.json

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+{
+  "dataset": "banknote-authentication",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Class",
+  "label_values": [
+    "2.0",
+    "1.0"
+  ],
+  "num_labels": 2,
+  "train_samples": 1234,
+  "test_samples": 138,
+  "train_label_distribution": {
+    "1.0": 685,
+    "2.0": 549
+  },
+  "test_label_distribution": {
+    "2.0": 61,
+    "1.0": 77
+  }
+}

classification/openml_cc18/banknote-authentication/test.csv

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classification/openml_cc18/banknote-authentication/test.jsonl

@@ -0,0 +1,138 @@
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+{"text": "The V1 is -1.03. The V2 is -6.39. The V3 is 5.53. The V4 is 0.8.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The V1 is -3.23. The V2 is -7.21. The V3 is 11.64. The V4 is -0.95.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.44. The V2 is 2.95. The V3 is 4.32. The V4 is 0.72.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
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+{"text": "The V1 is -3.59. The V2 is 0.23. The V3 is 0.71. The V4 is -0.33.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.32. The V2 is 3.17. The V3 is -1.0. The V4 is -2.72.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.69. The V2 is 10.82. The V3 is -3.3. The V4 is -4.29.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.19. The V2 is 4.55. The V3 is -4.98. The V4 is -2.73.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -3.56. The V2 is -8.38. The V3 is 12.39. The V4 is -1.28.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.94. The V2 is 5.86. The V3 is 1.88. The V4 is -0.33.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.47. The V2 is 2.29. The V3 is 0.96. The V4 is 0.83.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 3.73. The V2 is -3.88. The V3 is 3.36. The V4 is -0.01.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.4. The V2 is 6.89. The V3 is 1.06. The V4 is -0.68.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.66. The V2 is 7.64. The V3 is -2.42. The V4 is -1.24.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.59. The V2 is -1.06. The V3 is 3.89. The V4 is 0.78.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.56. The V2 is 3.36. The V3 is 2.03. The V4 is 0.27.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.79. The V2 is -8.12. The V3 is 7.09. The V4 is -1.21.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.31. The V2 is 3.67. The V3 is -0.7. The V4 is -1.25.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.13. The V2 is -2.04. The V3 is 2.56. The V4 is -0.06.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.91. The V2 is 4.05. The V3 is -0.46. The V4 is -4.03.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 1.1. The V2 is 0.64. The V3 is 5.99. The V4 is -0.58.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.72. The V2 is 9.08. The V3 is -3.31. The V4 is -0.97.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.83. The V2 is 3.07. The V3 is 0.69. The V4 is 0.81.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.13. The V2 is 6.12. The V3 is -2.43. The V4 is -0.2.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.12. The V2 is 0.22. The V3 is -0.47. The V4 is 0.97.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.3. The V2 is 10.27. The V3 is -2.95. The V4 is -5.86.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.05. The V2 is -1.6. The V3 is 8.48. The V4 is 0.76.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 3.94. The V2 is 10.16. The V3 is -3.82. The V4 is -4.02.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.77. The V2 is -7.45. The V3 is 6.49. The V4 is 0.36.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.71. The V2 is 2.08. The V3 is -0.27. The V4 is 1.24.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.79. The V2 is -5.71. The V3 is 5.95. The V4 is 0.46.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.8. The V2 is 11.88. The V3 is 2.05. The V4 is -5.27.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.56. The V2 is -3.63. The V3 is 2.87. The V4 is 0.28.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.72. The V2 is -0.05. The V3 is 5.67. The V4 is -1.35.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.57. The V2 is -0.96. The V3 is 2.71. The V4 is -0.17.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.04. The V2 is 1.52. The V3 is -1.41. The V4 is -0.76.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.45. The V2 is 12.62. The V3 is 0.74. The V4 is -7.66.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.57. The V2 is -0.02. The V3 is 1.24. The V4 is -0.56.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.19. The V2 is -1.25. The V3 is 2.26. The V4 is 0.77.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.13. The V2 is -1.15. The V3 is -0.95. The V4 is 0.58.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.83. The V2 is -9.04. The V3 is 9.07. The V4 is -0.98.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.57. The V2 is 10.11. The V3 is -1.69. The V4 is -4.39.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 4.31. The V2 is 8.21. The V3 is -2.78. The V4 is -1.43.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.67. The V2 is 5.66. The V3 is 0.73. The V4 is -1.49.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 1.86. The V2 is 3.21. The V3 is -0.16. The V4 is -0.26.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -5.87. The V2 is 9.18. The V3 is -0.27. The V4 is -6.04.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 5.75. The V2 is 10.18. The V3 is -4.79. The V4 is -4.34.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 0.55. The V2 is 10.38. The V3 is -1.54. The V4 is -4.16.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.57. The V2 is -4.41. The V3 is 5.99. The V4 is 0.08.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 3.55. The V2 is 9.37. The V3 is -4.04. The V4 is -3.96.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.71. The V2 is -5.56. The V3 is 4.05. The V4 is 0.9.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.56. The V2 is 9.27. The V3 is -3.59. The V4 is -1.36.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.67. The V2 is 3.06. The V3 is 0.37. The V4 is 0.59.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -4.84. The V2 is 6.68. The V3 is -0.24. The V4 is -6.58.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.94. The V2 is 7.41. The V3 is -0.98. The V4 is -0.88.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.71. The V2 is 2.8. The V3 is -2.38. The V4 is -2.35.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.21. The V2 is 9.22. The V3 is -3.7. The V4 is -6.81.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.58. The V2 is 9.75. The V3 is -3.17. The V4 is -3.0.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 6.56. The V2 is 9.82. The V3 is -4.41. The V4 is -3.23.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -5.53. The V2 is 6.33. The V3 is 0.9. The V4 is -6.62.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -2.46. The V2 is -0.24. The V3 is 1.4. The V4 is -0.46.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.73. The V2 is 2.02. The V3 is 7.76. The V4 is 0.94.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -1.28. The V2 is -2.41. The V3 is 4.57. The V4 is 0.48.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -3.72. The V2 is 1.9. The V3 is -0.04. The V4 is -2.51.", "label": "2.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is -0.64. The V2 is -4.61. The V3 is 8.35. The V4 is -2.71.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}
+{"text": "The V1 is 2.92. The V2 is 6.05. The V3 is -0.11. The V4 is -0.59.", "label": "1.0", "dataset": "banknote-authentication", "benchmark": "openml_cc18", "task_type": "clf"}

classification/openml_cc18/banknote-authentication/train.csv

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classification/openml_cc18/blood-transfusion-service-center/metadata.json

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+{
+  "dataset": "blood-transfusion-service-center",
+  "benchmark": "openml_cc18",
+  "sub_benchmark": "",
+  "task_type": "clf",
+  "data_type": "mixed",
+  "target_column": "Class",
+  "label_values": [
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+    "1.0"
+  ],
+  "num_labels": 2,
+  "train_samples": 673,
+  "test_samples": 75,
+  "train_label_distribution": {
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+    "2.0": 160
+  },
+  "test_label_distribution": {
+    "1.0": 57,
+    "2.0": 18
+  }
+}

classification/openml_cc18/blood-transfusion-service-center/test.csv

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