{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cf894f6f",
   "metadata": {},
   "source": [
    "# Intermediate Fusion mit Deep SVDD"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "494626b1",
   "metadata": {},
   "source": [
    "* Input: gemeinsames Dataset aus EYE Tracking und Action Units mit selber Abtastfrequenz\n",
    "* Verarbeitung: Intermediate Fusion\n",
    "* Modell: Deep SVDD --> Erlernen einer Kugel durch ein neuronales Netz, dass die Normaldaten einschließt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bef91203",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0b8274a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pathlib import Path\n",
    "import sys\n",
    "import os\n",
    "\n",
    "base_dir = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
    "sys.path.append(base_dir)\n",
    "print(base_dir)\n",
    "\n",
    "from Fahrsimulator_MSY2526_AI.model_training.tools import evaluation_tools, scaler, mad_outlier_removal\n",
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
    "from sklearn.svm import OneClassSVM\n",
    "from sklearn.model_selection import GridSearchCV, KFold, ParameterGrid, train_test_split, GroupKFold\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf\n",
    "import pickle\n",
    "from sklearn.metrics import (roc_auc_score, accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, classification_report, balanced_accuracy_score, ConfusionMatrixDisplay) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f00a477c",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "504c1df7",
   "metadata": {},
   "source": [
    "Laden der Daten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6482542b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_path = Path(r\"/home/jovyan/data-paulusjafahrsimulator-gpu/first_AU_dataset/output_windowed.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce8ab464",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_parquet(path=dataset_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b736bc58",
   "metadata": {},
   "source": [
    "### Modell Training"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa11faf3",
   "metadata": {},
   "source": [
    "Vor-Training der Gewichte mit Autoencoder, Loss: MSE"
   ]
  }
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