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  • Overview
  • Getting Started
  • Algorithm Overview
  • Saving and Loading
  • Detector Configuration Files
  • Outlier Detection
    • Methods
      • Mahalanobis Distance
      • Isolation Forest
      • Variational Auto-Encoder
      • Auto-Encoder
      • Variational Auto-Encoding Gaussian Mixture Model
      • Auto-Encoding Gaussian Mixture Model
      • Likelihood Ratios for Outlier Detection
      • Prophet Detector
      • Spectral Residual
      • Sequence-to-Sequence (Seq2Seq)
    • Examples
  • Drift Detection
  • Adversarial Detection
  • Deployment
  • Datasets
  • Models
  • Bibliography
  • API Reference
    • alibi_detect.ad
    • alibi_detect.base
    • alibi_detect.cd
    • alibi_detect.datasets
    • alibi_detect.exceptions
    • alibi_detect.models
    • alibi_detect.od
    • alibi_detect.saving
    • alibi_detect.utils
    • alibi_detect.version
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  1. Outlier Detection

Methods

Mahalanobis Distancechevron-rightIsolation Forestchevron-rightVariational Auto-Encoderchevron-rightAuto-Encoderchevron-rightVariational Auto-Encoding Gaussian Mixture Modelchevron-rightAuto-Encoding Gaussian Mixture Modelchevron-rightLikelihood Ratios for Outlier Detectionchevron-rightProphet Detectorchevron-rightSpectral Residualchevron-rightSequence-to-Sequence (Seq2Seq)chevron-right
PreviousOutlier Detectionchevron-leftNextMahalanobis Distancechevron-right

Last updated 1 year ago

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