simple ensemble method using random forest and AdaBoost

Stock_Price_Prediction(Updated).ipynb

@@ -5215,6 +5215,46 @@
         "plt.tight_layout()\n",
         "plt.show()\n"
       ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "This code demonstrates a simple ensemble method using random forest and AdaBoost. It combines the predictions of these two models by taking their average. You can experiment with different ensemble techniques like stacking or voting, and adjust the hyperparameters of the individual models to find the best combination for your specific problem."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from sklearn.ensemble import RandomForestRegressor, AdaBoostRegressor\n",
+        "from sklearn.model_selection import train_test_split\n",
+        "from sklearn.metrics import mean_squared_error\n",
+        "\n",
+        "# Assuming you have your features (X) and target variable (y)\n",
+        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+        "\n",
+        "# Create individual models\n",
+        "rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
+        "adaboost_model = AdaBoostRegressor(n_estimators=100, random_state=42)\n",
+        "\n",
+        "# Train the models\n",
+        "rf_model.fit(X_train, y_train)\n",
+        "adaboost_model.fit(X_train, y_train)\n",
+        "\n",
+        "# Make predictions\n",
+        "rf_predictions = rf_model.predict(X_test)\n",
+        "adaboost_predictions = adaboost_model.predict(X_test)\n",
+        "\n",
+        "# Combine predictions (simple averaging)\n",
+        "ensemble_predictions = (rf_predictions + adaboost_predictions) / 2\n",
+        "\n",
+        "# Evaluate the ensemble model\n",
+        "ensemble_mse = mean_squared_error(y_test, ensemble_predictions)\n",
+        "print(\"Ensemble MSE:\", ensemble_mse)"
+      ]
     }
   ],
   "metadata": {