{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "This code is straight from the colab cell. It will not run locally without modifying paths/imports to not use google drive etc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "haLQuFDzO1gG",
        "outputId": "3aacd5d1-be51-4fc7-c0db-113ce713814a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
            "✅ Google Drive mounted successfully!\n",
            "📁 Project folder set to: /content/drive/MyDrive/Colab Notebooks/Receipt/\n"
          ]
        }
      ],
      "source": [
        "# Import Necessary Libraries\n",
        "import os\n",
        "import pandas as pd\n",
        "import re\n",
        "from google.colab import drive\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import classification_report, accuracy_score, confusion_matrix\n",
        "\n",
        "# Mount Google Drive\n",
        "try:\n",
        "    drive.mount('/content/drive')\n",
        "    print(\"Google Drive mounted successfully\")\n",
        "except Exception as e:\n",
        "    print(f\"An error occurred while mounting Google Drive: {e}\")\n",
        "\n",
        "# Define File Paths\n",
        "BASE_DIRECTORY = '/content/drive/MyDrive/Colab Notebooks/Receipt/'\n",
        "\n",
        "# Paths for the raw data files\n",
        "INSTACART_PRODUCTS_FILE = os.path.join(BASE_DIRECTORY, 'products.csv')\n",
        "INSTACART_DEPARTMENTS_FILE = os.path.join(BASE_DIRECTORY, 'departments.csv')\n",
        "KAGGLE_RETAIL_FILE = os.path.join(BASE_DIRECTORY, 'train.csv')\n",
        "\n",
        "# The final, combined dataset that this notebook will create and use\n",
        "FINAL_DATASET_FILE = os.path.join(BASE_DIRECTORY, 'final_training_dataset.csv')\n",
        "\n",
        "print(f\"Project folder set to: {BASE_DIRECTORY}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4vL6xu74812w",
        "outputId": "e925c119-bdbc-4be3-8b4b-74a56aea195b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Processing Instacart dataset...\n",
            "\n",
            "Processing Kaggle Retail Products dataset...\n",
            "\n",
            "Combining datasets...\n",
            "\n",
            "🎉 Success! Combined dataset with 73661 items saved to '/content/drive/MyDrive/Colab Notebooks/Receipt/final_training_dataset.csv'.\n"
          ]
        }
      ],
      "source": [
        "# Define Mappings\n",
        "instacart_department_map = {\n",
        "    'produce': 'Food & Beverage', 'meat seafood': 'Food & Beverage', 'dairy eggs': 'Food & Beverage',\n",
        "    'bakery': 'Food & Beverage', 'frozen': 'Food & Beverage', 'pantry': 'Food & Beverage',\n",
        "    'canned goods': 'Food & Beverage', 'international': 'Food & Beverage', 'bulk': 'Food & Beverage',\n",
        "    'dry goods pasta': 'Food & Beverage', 'snacks': 'Food & Beverage', 'breakfast': 'Food & Beverage',\n",
        "    'beverages': 'Food & Beverage', 'alcohol': 'Food & Beverage', 'deli': 'Food & Beverage',\n",
        "    'personal care': 'Health & Beauty', 'household': 'Home & Garden', 'babies': 'Babies',\n",
        "    'pets': 'Pets', 'other': 'Miscellaneous', 'missing': 'Miscellaneous'\n",
        "}\n",
        "\n",
        "kaggle_category_map = {\n",
        "    'Clothing, Shoes & Jewelry': 'Apparel & Accessories', 'Electronics': 'Electronics & Media',\n",
        "    'Cell Phones & Accessories': 'Electronics & Media', 'Automotive': 'Automotive & Fuel',\n",
        "    'Health & Personal Care': 'Health & Beauty', 'Beauty': 'Health & Beauty',\n",
        "    'Tools & Home Improvement': 'Home & Garden', 'Patio, Lawn & Garden': 'Home & Garden',\n",
        "    'Grocery & Gourmet Food': 'Food & Beverage', 'Pet Supplies': 'Pets', 'Baby': 'Babies'\n",
        "}\n",
        "\n",
        "# Combine Datasets\n",
        "try:\n",
        "    print(\"Processing Instacart dataset...\")\n",
        "    products_df = pd.read_csv(INSTACART_PRODUCTS_FILE)\n",
        "    departments_df = pd.read_csv(INSTACART_DEPARTMENTS_FILE)\n",
        "    instacart_df = pd.merge(products_df, departments_df, on='department_id')\n",
        "    instacart_df['category'] = instacart_df['department'].map(instacart_department_map)\n",
        "    instacart_df.rename(columns={'product_name': 'description'}, inplace=True)\n",
        "    instacart_labeled = instacart_df[['description', 'category']].dropna()\n",
        "\n",
        "    print(\"\\nProcessing Kaggle Retail Products dataset...\")\n",
        "    kaggle_df = pd.read_csv(KAGGLE_RETAIL_FILE, usecols=['title', 'categories'])\n",
        "    kaggle_df['category'] = kaggle_df['categories'].map(kaggle_category_map)\n",
        "    kaggle_df.rename(columns={'title': 'description'}, inplace=True)\n",
        "    kaggle_labeled = kaggle_df[['description', 'category']].dropna()\n",
        "\n",
        "    print(\"\\nCombining datasets...\")\n",
        "    combined_df = pd.concat([instacart_labeled, kaggle_labeled], ignore_index=True)\n",
        "    combined_df.drop_duplicates(subset=['description'], inplace=True)\n",
        "    combined_df = combined_df[combined_df['description'].astype(str).str.len() > 1]\n",
        "\n",
        "    combined_df.to_csv(FINAL_DATASET_FILE, index=False)\n",
        "    print(f\"\\nSuccess. Combined dataset with {len(combined_df)} items saved to '{FINAL_DATASET_FILE}'.\")\n",
        "\n",
        "except FileNotFoundError as e:\n",
        "    print(f\"ERROR: A raw data file was not found. Please check your file paths. Details: {e}\")\n",
        "except Exception as e:\n",
        "    print(f\"An error occurred: {e}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YQO9hGBBAv27",
        "outputId": "096fe935-87c9-406f-dad5-9350e3dadda2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "✅ Successfully loaded 73661 items from the final dataset.\n",
            "✅ Text cleaning complete.\n",
            "✅ Data split into 58926 training and 14732 testing items.\n"
          ]
        }
      ],
      "source": [
        "try:\n",
        "    df = pd.read_csv(FINAL_DATASET_FILE)\n",
        "    print(f\"Successfully loaded {len(df)} items from the final dataset.\")\n",
        "except FileNotFoundError:\n",
        "    print(f\"ERROR: The file '{FINAL_DATASET_FILE}' was not found. Please run Cell 2 to create it.\")\n",
        "\n",
        "# Clean data\n",
        "def clean_text(text):\n",
        "    if not isinstance(text, str): text = ''\n",
        "    text = text.strip('\"').lower()\n",
        "    text = re.sub(r'[^a-z\\s]', '', text) # Keep only letters and spaces\n",
        "    text = ' '.join(text.split())\n",
        "    return text\n",
        "\n",
        "df['cleaned_description'] = df['description'].apply(clean_text)\n",
        "df.dropna(subset=['cleaned_description', 'category'], inplace=True)\n",
        "df = df[df['cleaned_description'] != '']\n",
        "print(\"Text cleaning complete.\")\n",
        "\n",
        "# Encode Labels and Split Data\n",
        "le = LabelEncoder()\n",
        "df['category_encoded'] = le.fit_transform(df['category'])\n",
        "\n",
        "X = df['cleaned_description']\n",
        "y = df['category_encoded']\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X, y, test_size=0.2, random_state=42, stratify=y\n",
        ")\n",
        "print(f\"Data split into {len(X_train)} training and {len(X_test)} testing items.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "38ofBynRICRY",
        "outputId": "4e6af48d-c678-4b07-9753-8525227b17af"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "✅ TF-IDF vectorization complete.\n",
            "Vocabulary size: 151376 terms\n",
            "✅ Model training complete.\n",
            "\n",
            "Overall Model Accuracy: 90.26%\n",
            "\n",
            "--- Classification Report: ---\n",
            "                       precision    recall  f1-score   support\n",
            "\n",
            "Apparel & Accessories       0.93      0.70      0.80       427\n",
            "    Automotive & Fuel       0.95      0.75      0.84       438\n",
            "               Babies       0.92      0.78      0.84       652\n",
            "  Electronics & Media       0.96      0.95      0.95       878\n",
            "      Food & Beverage       0.90      0.99      0.94      7670\n",
            "      Health & Beauty       0.89      0.88      0.89      2191\n",
            "        Home & Garden       0.87      0.85      0.86      1494\n",
            "        Miscellaneous       0.86      0.03      0.06       361\n",
            "                 Pets       0.96      0.83      0.89       621\n",
            "\n",
            "             accuracy                           0.90     14732\n",
            "            macro avg       0.91      0.75      0.79     14732\n",
            "         weighted avg       0.90      0.90      0.89     14732\n",
            "\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x900 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "💾 Saving model and vectorizer to: /content/drive/MyDrive/Colab Notebooks/Receipt/\n",
            "\n",
            "💾 Saving Label Encoder to: /content/drive/MyDrive/Colab Notebooks/Receipt/label_encoder.pkl\n",
            "✅ Label Encoder saved successfully.\n",
            "✅ Files saved successfully to your Google Drive.\n"
          ]
        }
      ],
      "source": [
        "import pickle\n",
        "# TF-IDF\n",
        "tfidf = TfidfVectorizer(ngram_range=(1, 2))\n",
        "X_train_tfidf = tfidf.fit_transform(X_train)\n",
        "X_test_tfidf = tfidf.transform(X_test)\n",
        "print(\"TF-IDF vectorization complete.\")\n",
        "print(f\"Vocabulary size: {len(tfidf.get_feature_names_out())} terms\")\n",
        "\n",
        "# Train Logistic Regression Model\n",
        "model = LogisticRegression(random_state=42, max_iter=2000)\n",
        "model.fit(X_train_tfidf, y_train)\n",
        "print(\"Model training complete.\")\n",
        "\n",
        "# Evaluate the Model Performance\n",
        "y_pred = model.predict(X_test_tfidf)\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "report = classification_report(y_test, y_pred, target_names=le.classes_)\n",
        "\n",
        "print(f\"\\nOverall Model Accuracy: {accuracy:.2%}\")\n",
        "print(\"\\n--- Classification Report: ---\")\n",
        "print(report)\n",
        "\n",
        "# Confusion Matrix\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "plt.figure(figsize=(12, 9))\n",
        "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues',\n",
        "            xticklabels=le.classes_, yticklabels=le.classes_)\n",
        "plt.title('Confusion Matrix', fontsize=16)\n",
        "plt.ylabel('Actual Category', fontsize=12)\n",
        "plt.xlabel('Predicted Category', fontsize=12)\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.yticks(rotation=0)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# Save Model and Vectorizer files\n",
        "\n",
        "vectorizer_path = os.path.join(BASE_DIRECTORY, 'tfidf_vectorizer.pkl')\n",
        "model_path = os.path.join(BASE_DIRECTORY, 'category_classifier.pkl')\n",
        "encoder_path = os.path.join(BASE_DIRECTORY, 'label_encoder.pkl')\n",
        "\n",
        "print(f\"\\n💾 Saving model and vectorizer to: {BASE_DIRECTORY}\")\n",
        "\n",
        "# Save vectorizer\n",
        "with open(vectorizer_path, 'wb') as f:\n",
        "    pickle.dump(tfidf, f)\n",
        "\n",
        "# Save model\n",
        "with open(model_path, 'wb') as f:\n",
        "    pickle.dump(model, f)\n",
        "\n",
        "print(f\"\\n💾 Saving Label Encoder to: {encoder_path}\")\n",
        "\n",
        "# Save encoder\n",
        "with open(encoder_path, 'wb') as f:\n",
        "    pickle.dump(le, f)\n",
        "\n",
        "print(\"✅ Label Encoder saved successfully.\")\n",
        "\n",
        "print(\"✅ Files saved successfully to your Google Drive.\")"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}