quality_predict.ipynb

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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install xgboost --upgrade\n",
        "!git clone https://github.com/kochlisGit/Wine-Preference-Analysis"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8uldAMNOhwas",
        "outputId": "03e08d46-b13a-481f-d4f9-349d6f46bf1c"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: xgboost in /usr/local/lib/python3.7/dist-packages (1.6.1)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from xgboost) (1.7.3)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from xgboost) (1.21.6)\n",
            "Cloning into 'Wine-Preference-Analysis'...\n",
            "remote: Enumerating objects: 127, done.\u001b[K\n",
            "remote: Counting objects: 100% (127/127), done.\u001b[K\n",
            "remote: Compressing objects: 100% (93/93), done.\u001b[K\n",
            "remote: Total 127 (delta 50), reused 82 (delta 30), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (127/127), 2.78 MiB | 28.16 MiB/s, done.\n",
            "Resolving deltas: 100% (50/50), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from ipywidgets.widgets import interactive, Dropdown, FloatSlider, IntSlider\n",
        "from IPython.display import display\n",
        "import joblib\n",
        "import numpy as np\n",
        "\n",
        "regressor = joblib.load('Wine-Preference-Analysis/checkpoints/xgboost_regressor.ckp')\n",
        "\n",
        "\n",
        "def predict(\n",
        "        wine_type: str,\n",
        "        fixed_acidity,\n",
        "        volatile_acidity,\n",
        "        citric_acid,\n",
        "        residual_sugar,\n",
        "        chlorides,\n",
        "        free_sulfur_dioxide,\n",
        "        other_sulfur_dioxide,\n",
        "        density,\n",
        "        ph,\n",
        "        sulphates,\n",
        "        alcohol\n",
        "):\n",
        "    wine_type_value = 0.0 if wine_type == 'White' else 1.0\n",
        "    sample = np.float64([[\n",
        "        wine_type_value, fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides,\n",
        "        free_sulfur_dioxide, other_sulfur_dioxide, density, ph, sulphates, alcohol\n",
        "    ]])\n",
        "    quality = regressor.predict(sample)[0]\n",
        "    display(f'Quality = {quality}')\n",
        "\n",
        "style = {'description_width': 'initial'}\n",
        "\n",
        "display(interactive(\n",
        "    predict,\n",
        "    wine_type=Dropdown(options=['White', 'Red'], style=style),\n",
        "    fixed_acidity=FloatSlider(value=7, min=4.0, max=16.0, style=style),\n",
        "    volatile_acidity=FloatSlider(value=0.35, min=0.0, max=1.6, style=style),\n",
        "    citric_acid=FloatSlider(value=0.35, min=0.0, max=1.7, style=style),\n",
        "    residual_sugar=IntSlider(value=5, min=1, max=66, style=style),\n",
        "    chlorides=FloatSlider(value=0.05, min=0.0, max=0.65, style=style),\n",
        "    free_sulfur_dioxide=IntSlider(value=30, min=1.0, max=290, style=style),\n",
        "    other_sulfur_dioxide=IntSlider(value=86, min=5.0, max=260, style=style),\n",
        "    density=FloatSlider(value=0.99, min=0.95, max=1.15, style=style),\n",
        "    ph=FloatSlider(value=3, min=2.5, max=16, style=style),\n",
        "    sulphates=FloatSlider(value=0.5, min=0.2, max=2, style=style),\n",
        "    alcohol=FloatSlider(value=10.5, min=3.0, max=15.0, style=style)\n",
        "))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419,
          "referenced_widgets": [
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        },
        "id": "CDBaaOIPa37u",
        "outputId": "52b3115a-8ad6-43dc-b7ee-79084ee37987"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "interactive(children=(Dropdown(description='wine_type', options=('White', 'Red'), style=DescriptionStyle(descr…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5a7947efd2d448e58ffd6110ae69767d"
            }
          },
          "metadata": {}
        }
      ]
    }
  ]
}