{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a179cd16ae91dee3",
   "metadata": {},
   "source": [
    "# Anomaly Detection\n",
    "\n",
    "This notebook shows some basic usage of CapyMOA for Anomaly Detection tasks.\n",
    "\n",
    "Algorithms: `HalfSpaceTrees`, `Autoencoder` and `Online Isolation Forest`\n",
    "\n",
    "Important notes: Prior to version 0.8.2, a lower anomaly score indicated a higher likelihood of an anomaly. This has been updated so that a higher anomaly score now indicates a higher likelihood of an anomaly, aligning with the standard anomaly detection literature.\n",
    "\n",
    "---\n",
    "\n",
    "*More information about CapyMOA can be found in* https://www.capymoa.org\n",
    "\n",
    "**last update on 10/01/2025**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4b151a3",
   "metadata": {},
   "source": [
    "## 1. Creating simple anomalous data with `sklearn`\n",
    "\n",
    "* Generating a few examples and some simple anomalous data using `sklearn`"
   ]
  },
  {
   "cell_type": "code",
   "id": "262e3e44",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:32:30.428385Z",
     "iopub.status.busy": "2024-09-23T00:32:30.427752Z",
     "iopub.status.idle": "2024-09-23T00:32:32.474012Z",
     "shell.execute_reply": "2024-09-23T00:32:32.473534Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:04:17.361762Z",
     "start_time": "2025-01-10T05:04:13.881120Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import make_blobs\n",
    "import matplotlib.pyplot as plt\n",
    "from capymoa.stream import NumpyStream\n",
    "\n",
    "# generate normal data points\n",
    "n_samples = 10000\n",
    "n_features = 2\n",
    "n_clusters = 3\n",
    "X, y = make_blobs(\n",
    "    n_samples=n_samples, n_features=n_features, centers=n_clusters, random_state=42\n",
    ")\n",
    "\n",
    "# generate anomalous data points\n",
    "n_anomalies = 100  # the anomaly rate is 1%\n",
    "anomalies = np.random.uniform(low=-10, high=10, size=(n_anomalies, n_features))\n",
    "\n",
    "# combine the normal data points with anomalies\n",
    "X = np.vstack([X, anomalies])\n",
    "y = np.hstack([y, [1] * n_anomalies])  # Label anomalies with 1\n",
    "y[:n_samples] = 0  # Label normal points with 0\n",
    "\n",
    "# shuffle the data\n",
    "idx = np.random.permutation(n_samples + n_anomalies)\n",
    "X = X[idx]\n",
    "y = y[idx]\n",
    "\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, cmap=\"viridis\")\n",
    "plt.show()\n",
    "\n",
    "# create a NumpyStream from the combined dataset\n",
    "feature_names = [f\"feature_{i}\" for i in range(n_features)]\n",
    "target_name = \"class\""
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "c190066b9765a7e7",
   "metadata": {},
   "source": [
    "## 2. Unsupervised Anomaly Detection for data streams\n",
    "\n",
    "* Recent research has been focused on unsupervised anomaly detection for data streams, as it is often difficult to obtain labeled data for training.\n",
    "* Instead of using evaluation functions, we first use a basic **test-then-train loop** from scratch to evaluate the model's performance.\n",
    "* Please notice that higher scores indicate higher anomaly likelihood."
   ]
  },
  {
   "cell_type": "code",
   "id": "8f7fd1e84afbb8a9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:32:32.475795Z",
     "iopub.status.busy": "2024-09-23T00:32:32.475616Z",
     "iopub.status.idle": "2024-09-23T00:32:33.435949Z",
     "shell.execute_reply": "2024-09-23T00:32:33.435465Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:04:18.835652Z",
     "start_time": "2025-01-10T05:04:17.418416Z"
    }
   },
   "source": [
    "from capymoa.anomaly import HalfSpaceTrees\n",
    "from capymoa.evaluation import AnomalyDetectionEvaluator\n",
    "\n",
    "stream_ad = NumpyStream(\n",
    "    X,\n",
    "    y,\n",
    "    dataset_name=\"AnomalyDetectionDataset\",\n",
    "    feature_names=feature_names,\n",
    "    target_name=target_name,\n",
    "    target_type=\"categorical\",\n",
    ")\n",
    "learner = HalfSpaceTrees(stream_ad.get_schema())\n",
    "evaluator = AnomalyDetectionEvaluator(stream_ad.get_schema())\n",
    "while stream_ad.has_more_instances():\n",
    "    instance = stream_ad.next_instance()\n",
    "    score = learner.score_instance(instance)\n",
    "    evaluator.update(instance.y_index, score)\n",
    "    learner.train(instance)\n",
    "\n",
    "auc = evaluator.auc()\n",
    "print(f\"AUC: {auc:.2f}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.94\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "id": "3fd96042",
   "metadata": {},
   "source": [
    "## 3. High-level evaluation functions\n",
    "\n",
    "* CapyMOA provides `prequential_evaluation_anomaly` as a high level function to assess Anomaly Detectors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a905343",
   "metadata": {},
   "source": [
    "### 3.1 ```prequential_evaluation_anomaly```\n",
    "In this example, we use the ```prequential_evaluation_anomaly``` function with ```plot_windowed_results``` to plot AUC for HalfSpaceTrees on the synthetic data stream"
   ]
  },
  {
   "cell_type": "code",
   "id": "06b462e8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:32:33.437850Z",
     "iopub.status.busy": "2024-09-23T00:32:33.437648Z",
     "iopub.status.idle": "2024-09-23T00:32:34.628764Z",
     "shell.execute_reply": "2024-09-23T00:32:34.628272Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:04:20.213970Z",
     "start_time": "2025-01-10T05:04:18.903109Z"
    }
   },
   "source": [
    "from capymoa.evaluation.visualization import plot_windowed_results\n",
    "from capymoa.anomaly import HalfSpaceTrees\n",
    "from capymoa.evaluation import prequential_evaluation_anomaly\n",
    "\n",
    "stream_ad = NumpyStream(\n",
    "    X,\n",
    "    y,\n",
    "    dataset_name=\"AnomalyDetectionDataset\",\n",
    "    feature_names=feature_names,\n",
    "    target_name=target_name,\n",
    "    target_type=\"categorical\",\n",
    ")\n",
    "hst = HalfSpaceTrees(schema=stream_ad.get_schema())\n",
    "\n",
    "results_hst = prequential_evaluation_anomaly(\n",
    "    stream=stream_ad, learner=hst, window_size=1000\n",
    ")\n",
    "\n",
    "print(f\"AUC: {results_hst.auc()}\")\n",
    "display(results_hst.windowed.metrics_per_window())\n",
    "plot_windowed_results(results_hst, metric=\"auc\", save_only=False)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.9415815\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "    instances       auc     s_auc  Accuracy     Kappa  Periodical holdout AUC  \\\n",
       "0      1000.0  0.849040  0.180372     0.060 -0.001022                0.000000   \n",
       "1      2000.0  0.945619  0.196099     0.007  0.000000                0.849040   \n",
       "2      3000.0  0.965010  0.215852     0.014  0.000000                0.945619   \n",
       "3      4000.0  0.927062  0.200816     0.006  0.000000                0.965010   \n",
       "4      5000.0  0.929814  0.185818     0.008  0.000000                0.927062   \n",
       "5      6000.0  0.944977  0.206376     0.013  0.000000                0.929814   \n",
       "6      7000.0  0.955576  0.207342     0.013  0.000000                0.944977   \n",
       "7      8000.0  0.972828  0.221292     0.010  0.000000                0.955576   \n",
       "8      9000.0  0.937626  0.216386     0.008  0.000000                0.972828   \n",
       "9     10000.0  0.976118  0.219181     0.009  0.000000                0.937626   \n",
       "10    10100.0  0.977778  0.222641     0.010  0.000000                0.976118   \n",
       "\n",
       "    Pos/Neg ratio    G-Mean  Recall      KappaM  \n",
       "0        0.010101  0.215322     0.9  -93.000000  \n",
       "1        0.007049  0.000000     1.0 -115.823529  \n",
       "2        0.014199  0.000000     1.0  -94.419355  \n",
       "3        0.006036  0.000000     1.0 -106.459459  \n",
       "4        0.008065  0.000000     1.0 -109.222222  \n",
       "5        0.013171  0.000000     1.0 -101.103448  \n",
       "6        0.013171  0.000000     1.0  -96.309859  \n",
       "7        0.010101  0.000000     1.0  -96.777778  \n",
       "8        0.008065  0.000000     1.0  -99.314607  \n",
       "9        0.009082  0.000000     1.0 -100.122449  \n",
       "10       0.010101  0.000000     1.0  -98.990000  "
      ],
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instances</th>\n",
       "      <th>auc</th>\n",
       "      <th>s_auc</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>Kappa</th>\n",
       "      <th>Periodical holdout AUC</th>\n",
       "      <th>Pos/Neg ratio</th>\n",
       "      <th>G-Mean</th>\n",
       "      <th>Recall</th>\n",
       "      <th>KappaM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.849040</td>\n",
       "      <td>0.180372</td>\n",
       "      <td>0.060</td>\n",
       "      <td>-0.001022</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.215322</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-93.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000.0</td>\n",
       "      <td>0.945619</td>\n",
       "      <td>0.196099</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.849040</td>\n",
       "      <td>0.007049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-115.823529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.965010</td>\n",
       "      <td>0.215852</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.945619</td>\n",
       "      <td>0.014199</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-94.419355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4000.0</td>\n",
       "      <td>0.927062</td>\n",
       "      <td>0.200816</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.965010</td>\n",
       "      <td>0.006036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-106.459459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.929814</td>\n",
       "      <td>0.185818</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.927062</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-109.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6000.0</td>\n",
       "      <td>0.944977</td>\n",
       "      <td>0.206376</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.929814</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-101.103448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7000.0</td>\n",
       "      <td>0.955576</td>\n",
       "      <td>0.207342</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.944977</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-96.309859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>0.972828</td>\n",
       "      <td>0.221292</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.955576</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-96.777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9000.0</td>\n",
       "      <td>0.937626</td>\n",
       "      <td>0.216386</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.972828</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-99.314607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>0.976118</td>\n",
       "      <td>0.219181</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.937626</td>\n",
       "      <td>0.009082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-100.122449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10100.0</td>\n",
       "      <td>0.977778</td>\n",
       "      <td>0.222641</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.976118</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-98.990000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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    {
     "data": {
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "id": "b5ce2efc-b595-4f6d-8b6c-d2dbcc01e527",
   "metadata": {},
   "source": [
    "## 3.2 Autoencoder"
   ]
  },
  {
   "cell_type": "code",
   "id": "63fd40e2-4c23-46bd-beb0-044a23b91447",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:32:34.630642Z",
     "iopub.status.busy": "2024-09-23T00:32:34.630439Z",
     "iopub.status.idle": "2024-09-23T00:32:40.681237Z",
     "shell.execute_reply": "2024-09-23T00:32:40.680753Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:04:25.849045Z",
     "start_time": "2025-01-10T05:04:20.303766Z"
    }
   },
   "source": [
    "from capymoa.evaluation.visualization import plot_windowed_results\n",
    "from capymoa.anomaly import Autoencoder\n",
    "from capymoa.evaluation import prequential_evaluation_anomaly\n",
    "\n",
    "stream_ad = NumpyStream(\n",
    "    X,\n",
    "    y,\n",
    "    dataset_name=\"AnomalyDetectionDataset\",\n",
    "    feature_names=feature_names,\n",
    "    target_name=target_name,\n",
    "    target_type=\"categorical\",\n",
    ")\n",
    "ae = Autoencoder(schema=stream_ad.get_schema(), hidden_layer=1)\n",
    "\n",
    "results_ae = prequential_evaluation_anomaly(\n",
    "    stream=stream_ad, learner=ae, window_size=1000\n",
    ")\n",
    "\n",
    "print(f\"AUC: {results_ae.auc()}\")\n",
    "display(results_ae.windowed.metrics_per_window())\n",
    "plot_windowed_results(results_ae, metric=\"auc\", save_only=False)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.54006\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "    instances       auc     s_auc  Accuracy     Kappa  Periodical holdout AUC  \\\n",
       "0      1000.0  0.477778  0.015538     0.989 -0.001821                0.000000   \n",
       "1      2000.0  0.545533  0.028975     0.993  0.000000                0.477778   \n",
       "2      3000.0  0.557664  0.000238     0.986  0.000000                0.545533   \n",
       "3      4000.0  0.615023  0.000008     0.994  0.000000                0.557664   \n",
       "4      5000.0  0.523438  0.000445     0.991 -0.001781                0.615023   \n",
       "5      6000.0  0.428727  0.009665     0.986 -0.001861                0.523438   \n",
       "6      7000.0  0.545554  0.000071     0.986 -0.001861                0.428727   \n",
       "7      8000.0  0.670808  0.061258     0.991  0.180328                0.545554   \n",
       "8      9000.0  0.597908  0.042223     0.991 -0.001781                0.670808   \n",
       "9     10000.0  0.588070  0.041752     0.991  0.000000                0.597908   \n",
       "10    10100.0  0.553131  0.037586     0.990  0.000000                0.588070   \n",
       "\n",
       "    Pos/Neg ratio    G-Mean  Recall    KappaM  \n",
       "0        0.010101  0.000000     0.0 -0.100000  \n",
       "1        0.007049  0.000000     0.0  0.176471  \n",
       "2        0.014199  0.000000     0.0 -0.354839  \n",
       "3        0.006036  0.000000     0.0  0.351351  \n",
       "4        0.008065  0.000000     0.0  0.000000  \n",
       "5        0.013171  0.000000     0.0 -0.448276  \n",
       "6        0.013171  0.000000     0.0 -0.380282  \n",
       "7        0.010101  0.316228     0.1  0.111111  \n",
       "8        0.008065  0.000000     0.0  0.089888  \n",
       "9        0.009082  0.000000     0.0  0.081633  \n",
       "10       0.010101  0.000000     0.0 -0.010000  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instances</th>\n",
       "      <th>auc</th>\n",
       "      <th>s_auc</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>Kappa</th>\n",
       "      <th>Periodical holdout AUC</th>\n",
       "      <th>Pos/Neg ratio</th>\n",
       "      <th>G-Mean</th>\n",
       "      <th>Recall</th>\n",
       "      <th>KappaM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.477778</td>\n",
       "      <td>0.015538</td>\n",
       "      <td>0.989</td>\n",
       "      <td>-0.001821</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000.0</td>\n",
       "      <td>0.545533</td>\n",
       "      <td>0.028975</td>\n",
       "      <td>0.993</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.477778</td>\n",
       "      <td>0.007049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.176471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.557664</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>0.986</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.545533</td>\n",
       "      <td>0.014199</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.354839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4000.0</td>\n",
       "      <td>0.615023</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.994</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.557664</td>\n",
       "      <td>0.006036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.351351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.523438</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>0.991</td>\n",
       "      <td>-0.001781</td>\n",
       "      <td>0.615023</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6000.0</td>\n",
       "      <td>0.428727</td>\n",
       "      <td>0.009665</td>\n",
       "      <td>0.986</td>\n",
       "      <td>-0.001861</td>\n",
       "      <td>0.523438</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.448276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7000.0</td>\n",
       "      <td>0.545554</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.986</td>\n",
       "      <td>-0.001861</td>\n",
       "      <td>0.428727</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.380282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>0.670808</td>\n",
       "      <td>0.061258</td>\n",
       "      <td>0.991</td>\n",
       "      <td>0.180328</td>\n",
       "      <td>0.545554</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9000.0</td>\n",
       "      <td>0.597908</td>\n",
       "      <td>0.042223</td>\n",
       "      <td>0.991</td>\n",
       "      <td>-0.001781</td>\n",
       "      <td>0.670808</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.089888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>0.588070</td>\n",
       "      <td>0.041752</td>\n",
       "      <td>0.991</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.597908</td>\n",
       "      <td>0.009082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10100.0</td>\n",
       "      <td>0.553131</td>\n",
       "      <td>0.037586</td>\n",
       "      <td>0.990</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.588070</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.010000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "id": "de4c8ccd-b29e-4c53-ae8d-923c6b9e0e5a",
   "metadata": {},
   "source": [
    "## 3.3 Online Isolation Forest"
   ]
  },
  {
   "cell_type": "code",
   "id": "28171920-a2d8-4c1e-bb2a-39d81079ebf8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:32:40.683004Z",
     "iopub.status.busy": "2024-09-23T00:32:40.682760Z",
     "iopub.status.idle": "2024-09-23T00:35:46.084849Z",
     "shell.execute_reply": "2024-09-23T00:35:46.084378Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:05:48.897097Z",
     "start_time": "2025-01-10T05:04:25.872681Z"
    }
   },
   "source": [
    "from capymoa.evaluation.visualization import plot_windowed_results\n",
    "from capymoa.anomaly import OnlineIsolationForest\n",
    "from capymoa.evaluation import prequential_evaluation_anomaly\n",
    "\n",
    "stream_ad = NumpyStream(\n",
    "    X,\n",
    "    y,\n",
    "    dataset_name=\"AnomalyDetectionDataset\",\n",
    "    feature_names=feature_names,\n",
    "    target_name=target_name,\n",
    "    target_type=\"categorical\",\n",
    ")\n",
    "oif = OnlineIsolationForest(schema=stream_ad.get_schema(), num_trees=10)\n",
    "\n",
    "results_oif = prequential_evaluation_anomaly(\n",
    "    stream=stream_ad, learner=oif, window_size=1000\n",
    ")\n",
    "\n",
    "print(f\"AUC: {results_oif.auc()}\")\n",
    "display(results_oif.windowed.metrics_per_window())\n",
    "plot_windowed_results(results_oif, metric=\"auc\", save_only=False)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.643632\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "    instances       auc     s_auc  Accuracy     Kappa  Periodical holdout AUC  \\\n",
       "0      1000.0  0.609091  0.111064     0.959  0.031649                0.000000   \n",
       "1      2000.0  0.767228  0.063018     0.993  0.000000                0.609091   \n",
       "2      3000.0  0.678463  0.060250     0.986  0.000000                0.767228   \n",
       "3      4000.0  0.680835  0.083064     0.994  0.000000                0.678463   \n",
       "4      5000.0  0.632560  0.057094     0.992  0.000000                0.680835   \n",
       "5      6000.0  0.632492  0.085781     0.987  0.000000                0.632560   \n",
       "6      7000.0  0.585457  0.043215     0.987  0.000000                0.632492   \n",
       "7      8000.0  0.789848  0.082476     0.990  0.000000                0.585457   \n",
       "8      9000.0  0.675025  0.069445     0.992  0.000000                0.789848   \n",
       "9     10000.0  0.649849  0.066430     0.991  0.000000                0.675025   \n",
       "10    10100.0  0.613182  0.059306     0.990  0.000000                0.649849   \n",
       "\n",
       "    Pos/Neg ratio    G-Mean  Recall    KappaM  \n",
       "0        0.010101  0.311075     0.1 -3.100000  \n",
       "1        0.007049  0.000000     0.0  0.176471  \n",
       "2        0.014199  0.000000     0.0 -0.354839  \n",
       "3        0.006036  0.000000     0.0  0.351351  \n",
       "4        0.008065  0.000000     0.0  0.111111  \n",
       "5        0.013171  0.000000     0.0 -0.344828  \n",
       "6        0.013171  0.000000     0.0 -0.281690  \n",
       "7        0.010101  0.000000     0.0  0.012346  \n",
       "8        0.008065  0.000000     0.0  0.191011  \n",
       "9        0.009082  0.000000     0.0  0.081633  \n",
       "10       0.010101  0.000000     0.0 -0.010000  "
      ],
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instances</th>\n",
       "      <th>auc</th>\n",
       "      <th>s_auc</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>Kappa</th>\n",
       "      <th>Periodical holdout AUC</th>\n",
       "      <th>Pos/Neg ratio</th>\n",
       "      <th>G-Mean</th>\n",
       "      <th>Recall</th>\n",
       "      <th>KappaM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.609091</td>\n",
       "      <td>0.111064</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.031649</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.311075</td>\n",
       "      <td>0.1</td>\n",
       "      <td>-3.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000.0</td>\n",
       "      <td>0.767228</td>\n",
       "      <td>0.063018</td>\n",
       "      <td>0.993</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.609091</td>\n",
       "      <td>0.007049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.176471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.678463</td>\n",
       "      <td>0.060250</td>\n",
       "      <td>0.986</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.767228</td>\n",
       "      <td>0.014199</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.354839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4000.0</td>\n",
       "      <td>0.680835</td>\n",
       "      <td>0.083064</td>\n",
       "      <td>0.994</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.678463</td>\n",
       "      <td>0.006036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.351351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.632560</td>\n",
       "      <td>0.057094</td>\n",
       "      <td>0.992</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.680835</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6000.0</td>\n",
       "      <td>0.632492</td>\n",
       "      <td>0.085781</td>\n",
       "      <td>0.987</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.632560</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.344828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7000.0</td>\n",
       "      <td>0.585457</td>\n",
       "      <td>0.043215</td>\n",
       "      <td>0.987</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.632492</td>\n",
       "      <td>0.013171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.281690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>0.789848</td>\n",
       "      <td>0.082476</td>\n",
       "      <td>0.990</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.585457</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.012346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9000.0</td>\n",
       "      <td>0.675025</td>\n",
       "      <td>0.069445</td>\n",
       "      <td>0.992</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.789848</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.191011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>0.649849</td>\n",
       "      <td>0.066430</td>\n",
       "      <td>0.991</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.675025</td>\n",
       "      <td>0.009082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10100.0</td>\n",
       "      <td>0.613182</td>\n",
       "      <td>0.059306</td>\n",
       "      <td>0.990</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.649849</td>\n",
       "      <td>0.010101</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.010000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "id": "2f979d3b-021b-48a0-95c5-7066b92895a4",
   "metadata": {},
   "source": [
    "## 4 Comparing algorithms"
   ]
  },
  {
   "cell_type": "code",
   "id": "c5e81e61-7a9f-4f6d-a4df-415a25bf2b03",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T00:35:46.086620Z",
     "iopub.status.busy": "2024-09-23T00:35:46.086421Z",
     "iopub.status.idle": "2024-09-23T00:35:46.197186Z",
     "shell.execute_reply": "2024-09-23T00:35:46.196713Z"
    },
    "ExecuteTime": {
     "end_time": "2025-01-10T05:05:49.073531Z",
     "start_time": "2025-01-10T05:05:48.932032Z"
    }
   },
   "source": [
    "plot_windowed_results(\n",
    "    results_hst, results_ae, results_oif, metric=\"auc\", save_only=False\n",
    ")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 6
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "capymoa",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}