ch7_random_forest_regression.ipynb

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        "<a href=\"https://colab.research.google.com/github/ThatNinjaGuy/Machine-learning-A-Z-Course/blob/develop/ch7_random_forest_regression.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "# Random Forest Regression"
      ]
    },
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      "cell_type": "markdown",
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      "source": [
        "## Importing the libraries"
      ]
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    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd"
      ],
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      },
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      "outputs": []
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      "source": [
        "## Importing the dataset"
      ]
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      "cell_type": "code",
      "source": [
        "dataset = pd.read_csv('Position_Salaries.csv')\n",
        "X = dataset.iloc[:, 1:-1].values\n",
        "y = dataset.iloc[:, -1].values"
      ],
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      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
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      },
      "source": [
        "## Training the Random Forest Regression model on the whole dataset"
      ]
    },
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      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "regressor = RandomForestRegressor(n_estimators = 10, random_state = 0)\n",
        "regressor.fit(X, y)"
      ],
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              "RandomForestRegressor(n_estimators=10, random_state=0)"
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      "source": [
        "## Predicting a new result"
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        "regressor.predict([[6.5], [7.5]])"
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        "plt.scatter(X, y, color = 'red')\n",
        "plt.plot(X, regressor.predict(X), color = 'blue')\n",
        "plt.title('Truth or Bluff (Random Forest Regression)')\n",
        "plt.xlabel('Position level')\n",
        "plt.ylabel('Salary')\n",
        "plt.show"
      ],
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              "\n",
              "Parameters\n",
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              "    are closed.\n",
              "\n",
              "    If `False` ensure that all figure windows are displayed and return\n",
              "    immediately.  In this case, you are responsible for ensuring\n",
              "    that the event loop is running to have responsive figures.\n",
              "\n",
              "    Defaults to True in non-interactive mode and to False in interactive\n",
              "    mode (see `.pyplot.isinteractive`).\n",
              "\n",
              "See Also\n",
              "--------\n",
              "ion : Enable interactive mode, which shows / updates the figure after\n",
              "      every plotting command, so that calling ``show()`` is not necessary.\n",
              "ioff : Disable interactive mode.\n",
              "savefig : Save the figure to an image file instead of showing it on screen.\n",
              "\n",
              "Notes\n",
              "-----\n",
              "**Saving figures to file and showing a window at the same time**\n",
              "\n",
              "If you want an image file as well as a user interface window, use\n",
              "`.pyplot.savefig` before `.pyplot.show`. At the end of (a blocking)\n",
              "``show()`` the figure is closed and thus unregistered from pyplot. Calling\n",
              "`.pyplot.savefig` afterwards would save a new and thus empty figure. This\n",
              "limitation of command order does not apply if the show is non-blocking or\n",
              "if you keep a reference to the figure and use `.Figure.savefig`.\n",
              "\n",
              "**Auto-show in jupyter notebooks**\n",
              "\n",
              "The jupyter backends (activated via ``%matplotlib inline``,\n",
              "``%matplotlib notebook``, or ``%matplotlib widget``), call ``show()`` at\n",
              "the end of every cell by default. Thus, you usually don&#x27;t have to call it\n",
              "explicitly there.</pre>\n",
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kLqF9yMbYTon"
      },
      "source": [
        "## Visualising the Random Forest Regression results (higher resolution)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_grid = np.arange(min(X), max(X), 0.1)\n",
        "X_grid = X_grid.reshape((len(X_grid), 1))\n",
        "plt.scatter(X, y, color = 'red')\n",
        "plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')\n",
        "plt.title('Truth or Bluff (Random Forest Regression)')\n",
        "plt.xlabel('Position level')\n",
        "plt.ylabel('Salary')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "id": "n33iA37YZvyu",
        "outputId": "683cbd26-f354-473e-98b9-c7cbf2eda1c6"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-19-7673de894480>:1: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
            "  X_grid = np.arange(min(X), max(X), 0.1)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}