ELKI Data Mining Toolkit
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
🔗 Methods for Correlation Analysis
pca: A Python Package for Principal Component Analysis.
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
Streaming anomaly detection in Python: online detectors (xStream, LODA, RS-Hash, Half-Space Trees, RRCF…) plus calibration and prequential evaluation for real-time data.
Open-source framework to detect outliers in Elasticsearch events
Image Mosaicing or Panorama Creation
RADseq Data Exploration, Manipulation and Visualization using R
Deep Learning for Anomaly Deteection
Utility library for detecting and removing outliers from normally distributed datasets using the Smirnov-Grubbs test.
2D Outlier Analysis using Shiny
Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters
Beyond Outlier Detection: LookOut for Pictorial Explanation
Imputation of Financial Time Series with Missing Values and/or Outliers
An implementation of Isolation forest
[ICML 2024] Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
Genie: A Fast and Robust Hierarchical Clustering Algorithm (this R package has now been superseded by genieclust)
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