defined the helper functions

decision_tree/decision_tree.ipynb

@@ -192,7 +192,26 @@
     "            \"right\": self._build_tree(X[right_indices], y[right_indices], depth + 1)\n",
     "        }\n",
     "        \n",
-    "        \n"
+    "    def _find_best_split(self, X, y, n_features):\n",
+    "        best_feature = None\n",
+    "        best_threshold = None\n",
+    "        best_impurity = float('inf')\n",
+    "\n",
+    "        for feature_index in range(n_features):\n",
+    "            thresholds = np.unique(X[:, feature_index])\n",
+    "            for threshold in thresholds:\n",
+    "                impurity = gini_split(X, y, feature_index, threshold)\n",
+    "                if impurity < best_impurity:\n",
+    "                    best_feature = feature_index\n",
+    "                    best_threshold = threshold\n",
+    "                    best_impurity = impurity\n",
+    "\n",
+    "        return best_feature, best_threshold\n",
+    "    \n",
+    "    def _most_common_label(self, y):\n",
+    "        return Counter(y).most_common(1)[0][0]\n",
+    "    \n",
+    "    \n"
    ]
   }
  ],