96 lines (96 with data), 63.7 kB

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Example F1 scores for each model, class, and category\n",
        "f1_scores_nsclc_0 = [0.84, 0.82, 0.77, 0.82, 0.82]  # F1 scores for NSCLC class 0.0\n",
        "f1_scores_nsclc_1 = [0.80, 0.76, 0.79, 0.81, 0.81]  # F1 scores for NSCLC class 1.0\n",
        "f1_scores_sclc_0 = [0.85, 0.86, 0.71, 0.83, 0.83]  # F1 scores for SCLC class 0.0\n",
        "f1_scores_sclc_1 = [0.83, 0.82, 0.72, 0.80, 0.82]  # F1 scores for SCLC class 1.0\n",
        "\n",
        "# Model names\n",
        "models = ['Random Forest', 'K Nearest Neighbors', 'Logistic Regression', 'AdaBoost', 'Gradient Boost']\n",
        "\n",
        "# Set up the bar plot\n",
        "x = np.arange(len(models))  # the label locations\n",
        "width = 0.15  # the width of the bars\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(15, 8))\n",
        "rects1 = ax.bar(x - 2*width, f1_scores_sclc_0, width, label='SCLC Class 0.0', color='#040354')\n",
        "rects2 = ax.bar(x - width, f1_scores_sclc_1, width, label='SCLC Class 1.0', color='#C3C2EC')\n",
        "rects3 = ax.bar(x, f1_scores_nsclc_0, width, label='NSCLC Class 0.0', color='#2693B0')\n",
        "rects4 = ax.bar(x + width, f1_scores_nsclc_1, width, label='NSCLC Class 1.0', color='orange')\n",
        "\n",
        "# Add some text for labels, title, and custom x-axis tick labels, etc.\n",
        "ax.set_ylabel('F1 Scores')\n",
        "ax.set_title('F1 Scores by Model, Class, and Category')\n",
        "ax.set_xticks(x)\n",
        "ax.set_xticklabels(models)\n",
        "\n",
        "# Move the legend outside of the plot\n",
        "ax.legend(loc='upper left', bbox_to_anchor=(1, 1))\n",
        "\n",
        "# Function to attach a label above each bar\n",
        "def autolabel(rects):\n",
        "    for rect in rects:\n",
        "        height = rect.get_height()\n",
        "        ax.annotate('{}'.format(height),\n",
        "                    xy=(rect.get_x() + rect.get_width() / 2, height),\n",
        "                    xytext=(0, 3),  # 3 points vertical offset\n",
        "                    textcoords=\"offset points\",\n",
        "                    ha='center', va='bottom')\n",
        "\n",
        "# Call the autolabel function for each set of bars\n",
        "autolabel(rects1)\n",
        "autolabel(rects2)\n",
        "autolabel(rects3)\n",
        "autolabel(rects4)\n",
        "\n",
        "# Adjust layout to make room for the legend\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plot\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 808
        },
        "id": "8XGMJhVrAWes",
        "outputId": "649c4799-8a7a-484c-ae0d-f62511ff2432"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x800 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}