extract_params.lhss

<p>Obtain parameters from a <code>lhss</code> object</p>

internal

Fast, flexible and user-friendly tools for distribution comparison
through direct density ratio estimation. The estimated density ratio can be
used for covariate shift adjustment, outlier-detection, change-point detection,
classification and evaluation of synthetic data quality. The package implements
multiple non-parametric estimation techniques (unconstrained least-squares
importance fitting, ulsif(), Kullback-Leibler importance estimation procedure,
kliep(), spectral density ratio estimation, spectral(), kernel mean matching,
kmm(), and least-squares hetero-distributional subspace search, lhss()).
with automatic tuning of hyperparameters. Helper functions are available for
two-sample testing and visualizing the density ratios. For an overview on
density ratio estimation, see Sugiyama et al. (2012) <doi:10.1017/CBO9781139035613>
for a general overview, and the help files for references on the specific
estimation techniques.

Thom Volker

densityratio

Distribution Comparison Through Density Ratio Estimation

Carlos Gonzalez Poses

Erik-Jan van Kesteren

extract_params.lhss function

Obtain parameters from a lhss object — extract_params.lhss

Obtain parameters from a <code>lhss</code> object

extract_params.lhss: Obtain parameters from a `lhss` object

Description

Usage

Arguments