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.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+anomaly_detection_results/data_visualization.png filter=lfs diff=lfs merge=lfs -text
+anomaly_detection_results/methods_comparison.png filter=lfs diff=lfs merge=lfs -text
+anomaly_detection_results/training_progress.png filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Jupyter Notebook Checkpoints
+.ipynb_checkpoints/ 

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anomaly_detection_results/project_structure.json

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+  "project_name": "Anomaly Detection Suite",
+  "creation_date": "2025-07-15T17:11:08.700607",
+  "total_files": 31,
+  "files_created": [
+    "autoencoder_config.json",
+    "autoencoder_model.pth",
+    "autoencoder_predictions.npy",
+    "autoencoder_results.json",
+    "autoencoder_scaler.pkl",
+    "autoencoder_scores.npy",
+    "autoencoder_training.json",
+    "data_split_info.json",
+    "data_visualization.png",
+    "dataset_X.npy",
+    "dataset_info.json",
+    "dataset_y.npy",
+    "final_summary.json",
+    "isolation_forest_model.pkl",
+    "isolation_forest_predictions.npy",
+    "isolation_forest_results.json",
+    "isolation_forest_scores.npy",
+    "lof_predictions.npy",
+    "lof_results.json",
+    "lof_scores.npy",
+    "methods_comparison.png",
+    "one_class_svm_model.pkl",
+    "one_class_svm_predictions.npy",
+    "one_class_svm_results.json",
+    "one_class_svm_scores.npy",
+    "statistical_predictions.npy",
+    "statistical_results.json",
+    "statistical_scaler.pkl",
+    "statistical_scores.npy",
+    "svm_scaler.pkl",
+    "training_progress.png"
+  ],
+  "file_descriptions": {
+    "dataset_X.npy": "Feature matrix of the synthetic dataset",
+    "dataset_y.npy": "Labels for the synthetic dataset",
+    "dataset_info.json": "Dataset metadata and statistics",
+    "data_visualization.png": "Visualization of the dataset distribution",
+    "statistical_*.npy": "Statistical method predictions and scores",
+    "statistical_results.json": "Statistical method results and metadata",
+    "isolation_forest_model.pkl": "Trained Isolation Forest model",
+    "isolation_forest_*.npy": "Isolation Forest predictions and scores",
+    "isolation_forest_results.json": "Isolation Forest results and metadata",
+    "one_class_svm_model.pkl": "Trained One-Class SVM model",
+    "svm_scaler.pkl": "Scaler used for SVM preprocessing",
+    "one_class_svm_*.npy": "SVM predictions and scores",
+    "one_class_svm_results.json": "SVM results and metadata",
+    "lof_*.npy": "LOF predictions and scores",
+    "lof_results.json": "LOF results and metadata",
+    "autoencoder_model.pth": "Trained autoencoder model with full state",
+    "autoencoder_scaler.pkl": "Scaler used for autoencoder preprocessing",
+    "autoencoder_config.json": "Autoencoder architecture configuration",
+    "autoencoder_training.json": "Training history and hyperparameters",
+    "autoencoder_*.npy": "Autoencoder predictions and scores",
+    "autoencoder_results.json": "Autoencoder results and metadata",
+    "methods_comparison.png": "Visual comparison of all methods",
+    "training_progress.png": "Autoencoder training loss progression",
+    "final_summary.json": "Comprehensive results summary",
+    "project_structure.json": "This file - project structure information"
+  }
+}

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+  "method": "Statistical Z-score",
+  "threshold": 2.5,
+  "auc_score": 1.0,
+  "anomalies_detected": 26,
+  "training_samples": 700,
+  "test_samples": 300
+}

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