Update README.md

README.md

@@ -34,7 +34,6 @@ dataset_info:
         names:
           0: 0
           1: 1 
-
 ---
 
 # Hematotoxicity Dataset (HematoxLong2022)
@@ -99,20 +98,19 @@ then load, featurize, split, fit, and evaluate the a catboost model
       representations = load_representations_from_dicts([{"name": "morgan"}, {"name": "maccs_rdkit"}]))
 
     model = load_model_from_dict({
-        "name": "cat_boost__regressor",
+        "name": "cat_boost_classifier",
         "config": {
             "x_features": ['smiles::morgan', 'smiles::maccs_rdkit'],
-            "y_features": ['log_solubility'],
-        })
-        
+            "y_features": ['0/1']}})
+    
     model.train(split_featurised_dataset["train"])
     preds = model.predict(split_featurised_dataset["test"])
     
-    regression_suite = load_suite("regression")
+    classification_suite = load_suite("classification")
     
-    scores = regression_suite.compute(
-        references=split_featurised_dataset["test"]['Solubility'],
-        predictions=preds["cat_boost_regressor::Solubility"])
+    scores = classification_suite.compute(
+        references=split_featurised_dataset["test"]['0/1-'],
+        predictions=preds["cat_boost_classifier::0/1-"])        
 
 ## Citation
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