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{
"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"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.12.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}