Welcome to quick-anomaly-detector’s documentation!
quick-anomaly-detector is a Python library that provides a collection of classes to model an anomaly detection task.
Check out the Quick Start section for further information.
- Quick Start
- Data Process
- quick_anomaly_detector.data_process.apply_transformations
- quick_anomaly_detector.data_process.calculate_metrics
- quick_anomaly_detector.data_process.check_valid_tensor_data
- quick_anomaly_detector.data_process.graph_scatter
- quick_anomaly_detector.data_process.graph_multiple_histograms
- quick_anomaly_detector.data_process.category_hist_graph
- quick_anomaly_detector.data_process.check_wrong
- quick_anomaly_detector.data_process.parse_dates
- Models
- quick_anomaly_detector.models.AnomalyGaussianModel
- quick_anomaly_detector.models.TrainAnomalyNN
- quick_anomaly_detector.models.TrainEmbedding
- quick_anomaly_detector.models.TrainClassificationNN
- quick_anomaly_detector.models.trainXGB
- quick_anomaly_detector.models.KMeansModel
- quick_anomaly_detector.models.ImputerNa
- quick_anomaly_detector.models.SelectFeatures
- quick_anomaly_detector.models.LowerStr
- quick_anomaly_detector.models.LengthStr
- quick_anomaly_detector.models.LogTransform
- quick_anomaly_detector.models.NumericDataType
- quick_anomaly_detector.models.Padding
- Pipeline
Additional Information
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Usage Example
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