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https://github.com/JuliaStats/MultivariateStats.jl

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
https://github.com/JuliaStats/MultivariateStats.jl

cca dimensionality-reduction ica isotonic-regression julia lda linear-regression mds multivariate-statistics ols-regression pca regression ridge-regression statistics

Last synced: 12 days ago
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A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Host: GitHub
URL: https://github.com/JuliaStats/MultivariateStats.jl
Owner: JuliaStats
License: other
Created: 2014-03-12T21:59:49.000Z (about 10 years ago)
Default Branch: master
Last Pushed: 2024-01-19T12:09:34.000Z (4 months ago)
Last Synced: 2024-03-26T13:28:05.669Z (about 2 months ago)
Topics: cca, dimensionality-reduction, ica, isotonic-regression, julia, lda, linear-regression, mds, multivariate-statistics, ols-regression, pca, regression, ridge-regression, statistics
Language: Julia
Homepage:
Size: 1.32 MB
Stars: 365
Watchers: 27
Forks: 84
Open Issues: 47
Metadata Files:
- Readme: README.md
- License: LICENSE.md

Lists

AI - MultivariateStats - Methods for dimensionality reduction. (Julia / [Tools](#tools-1))
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia / [Tools](#tools-1))
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia)
awesome-machine-learnings - MultivariateStats - Methods for dimensionality reduction. (Julia / [Tools](#tools-1))
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia / [Tools](#tools-1))
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia / [Tools](#tools-1))
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia / Tools)
awesome-machine-learning - MultivariateStats - Methods for dimensionality reduction. (Julia / Tools)

README

        # Multivariate Statistics

A Julia package for multivariate statistics and data analysis (e.g. dimensionality reduction).

[![Coverage Status](https://coveralls.io/repos/JuliaStats/MultivariateStats.jl/badge.svg?branch=master)](https://coveralls.io/r/JuliaStats/MultivariateStats.jl?branch=master)

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

[![CI](https://github.com/JuliaStats/MultivariateStats.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/JuliaStats/MultivariateStats.jl/actions/workflows/ci.yml)

[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://juliastats.org/MultivariateStats.jl/stable)

[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://juliastats.org/MultivariateStats.jl/dev)

## Functionalities

#### Available

- Linear Least Square Regression

- Ridge Regression

- Isotonic Regression

- Data Whitening

- Principal Components Analysis (PCA)

- Canonical Correlation Analysis (CCA)

- Classical Multidimensional Scaling (MDS)

- Metric Multidimensional Scaling (mMDS)

- Linear Discriminant Analysis (LDA)

- Multi-class LDA

- Independent Component Analysis (FastICA)

- Probabilistic PCA

- Factor Analysis

- Kernel PCA

#### Future Plan

- Partial Least Square (PLS)

- Other algorithms for ICA (*e.g.* JADE)