Models

quick-anomaly-detector.models includs the model class and train model class.

models.AnomalyGaussianModel([features, label])

Anomaly Gaussian Model using Gaussian Distribution.

models.TrainAnomalyNN([lr, num_epochs, patience])

Class for training and using an anomaly detection neural network.

models.TrainEmbedding([lr, num_epochs, ...])

models.TrainClassificationNN([lr, ...])

models.trainXGB([num_epochs, patience, lr, ...])

Train XGB model

models.KMeansModel([K])

The KMeansModel class is a Python implementation of the K-means clustering algorithm.

models.ImputerNa([strategy, fill_values])

A custom imputer transformer that extends scikit-learn's SimpleImputer while preserving column names after imputation.

models.SelectFeatures([features, label])

This class is for pipeline using of select features and label

models.LowerStr([features])

This class is for pipeline using of make the string value to lower letter.

models.LengthStr([features])

This class is for pipeline using of make the string value to lower letter.

models.LogTransform([features])

This class is for pipeline using of calculate log.

models.NumericDataType([features])

This class is for set data into numberic datatype.

models.Padding(features[, max_lengths])

This class is for data pipeline that padding for str columns