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https://github.com/trappmartin/hilbertschmidtindependencecriterion.jl

Julia implementations of the Hilbert-Schmidt Independence Criterion (HSIC)
https://github.com/trappmartin/hilbertschmidtindependencecriterion.jl

hilbert-spaces independence julia

Last synced: 3 months ago
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Julia implementations of the Hilbert-Schmidt Independence Criterion (HSIC)

Host: GitHub
URL: https://github.com/trappmartin/hilbertschmidtindependencecriterion.jl
Owner: trappmartin
License: other
Created: 2016-01-27T14:44:14.000Z (almost 9 years ago)
Default Branch: master
Last Pushed: 2019-05-14T11:10:27.000Z (over 5 years ago)
Last Synced: 2024-10-10T11:06:54.539Z (3 months ago)
Topics: hilbert-spaces, independence, julia
Language: Julia
Size: 14.6 KB
Stars: 5
Watchers: 1
Forks: 3
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE.md

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README

        [![Build Status](https://travis-ci.org/trappmartin/HilbertSchmidtIndependenceCriterion.jl.svg?branch=master)](https://travis-ci.org/trappmartin/HilbertSchmidtIndependenceCriterion.jl)

[![Coverage Status](https://coveralls.io/repos/github/trappmartin/HilbertSchmidtIndependenceCriterion.jl/badge.svg?branch=master)](https://coveralls.io/github/trappmartin/HilbertSchmidtIndependenceCriterion.jl?branch=master)

# Hilbert-Schmidt Independence Criterion (HSIC)

This package provides basic implementations of the Hilbert-Schmidt Independence Criterion (HSIC) for Julia 1.0.

## What is implemented

The package currently contains the following implementations:

- Gamma HSIC (HSIC with Gamma approximation) [1]

## Example

The gamma HSIC can be run using:

```julia

X = randn(1, 100) # rows are samples

Y = randn(1, 100) * 0.2 # rows are samples

p = 0.1 # p-value (level of test)

(value, threshold) = gammaHSIC(X, Y, α = p)

independent = value < threshold

```

## Reference

[1] Gretton, Arthur, et al. "A kernel statistical test of independence." Advances in Neural Information Processing Systems. 2007.