report edit

notebooks/07_support_vector_machine.ipynb

@@ -767,7 +767,7 @@
         "print(f\"  - Max Iterations: {svm_classifier.max_iter}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/08_k_nearest_neighbors.ipynb

@@ -580,7 +580,7 @@
         "print(f\"  - Best CV F1-Score: {random_search.best_score_:.4f}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/09_decision_trees.ipynb

@@ -701,7 +701,7 @@
         "print(f\"  - Min Samples Leaf: {dt_classifier.min_samples_leaf}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/10_random_forest.ipynb

@@ -712,7 +712,7 @@
         "print(f\"  - Max Features: {rf_classifier.max_features}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/11_stochastic_gradient_descent.ipynb

@@ -768,7 +768,7 @@
         "print(f\"  - Early Stopping: {sgd_classifier.early_stopping}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/12_xgboost.ipynb

@@ -735,7 +735,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "24",
    "metadata": {
     "colab": {
@@ -793,7 +793,7 @@
     "print(f\"  - Min Child Weight: {xgb_classifier.min_child_weight}\")\n",
     "print(f\"\\nFeature Engineering:\")\n",
     "print(f\"  - Vectorizer: TF-IDF\")\n",
-    "print(f\"  - Max Features: 5000\")\n",
+    "print(f\"  - Max Features: 100000\")\n",
     "print(f\"  - N-gram Range: (1, 2)\")\n",
     "print(f\"  - Min Document Frequency: 5\")\n",
     "print(f\"  - Max Document Frequency: 0.8\")\n",

notebooks/13_lightgbm.ipynb

@@ -739,7 +739,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 17,
+      "execution_count": null,
       "id": "24",
       "metadata": {
         "colab": {
@@ -798,7 +798,7 @@
         "print(f\"  - Colsample by Tree: {lgb_classifier.colsample_bytree}\")\n",
         "print(f\"\\nFeature Engineering:\")\n",
         "print(f\"  - Vectorizer: TF-IDF\")\n",
-        "print(f\"  - Max Features: 5000\")\n",
+        "print(f\"  - Max Features: 100000\")\n",
         "print(f\"  - N-gram Range: (1, 2)\")\n",
         "print(f\"  - Min Document Frequency: 5\")\n",
         "print(f\"  - Max Document Frequency: 0.8\")\n",