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isotree (version 0.1.8)

Isolation-Based Outlier Detection

Description

Fast and multi-threaded implementation of isolation forest (Liu, Ting, Zhou (2008) ), extended isolation forest (Hariri, Kind, Brunner (2018) ), SCiForest (Liu, Ting, Zhou (2010) ), and fair-cut forest (Cortes (2019) ), for isolation-based outlier detection, clustered outlier detection, distance or similarity approximation (Cortes (2019) ), and imputation of missing values (Cortes (2019) ), based on random or guided decision tree splitting. Provides simple heuristics for fitting the model to categorical columns and handling missing data, and offers options for varying between random and guided splits, and for using different splitting criteria.

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Install

install.packages('isotree')

Monthly Downloads

1,134

Version

0.1.8

License

BSD_2_clause + file LICENSE

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Maintainer

David Cortes

Last Published

January 8th, 2020

Functions in isotree (0.1.8)

isolation.forest

Isolation Forest model
predict.isolation_forest

Predict method for Isolation Forest
summary.isolation_forest

Print summary information from Isolation Forest model
unpack.isolation.forest

Unpack isolation forest model after de-serializing
add.isolation.tree

Add additional (single) tree to isolation forest model
print.isolation_forest

Print summary information from Isolation Forest model