Gaussian Mixture Model implementation #369
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…determinant, SparseVector.subtract.
oracle-contributor-agreement
bot
added
the
OCA Verified
Math/src/main/java/org/tribuo/math/distributions/MultivariateNormalDistribution.java
Show resolved
Hide resolved
Math/src/main/java/org/tribuo/math/distributions/MultivariateNormalDistribution.java
Show resolved
Hide resolved
Clustering/GMM/src/main/java/org/tribuo/clustering/gmm/GaussianMixtureModel.java
Show resolved
Hide resolved
JackSullivan
requested changes
Dec 17, 2024
|
I've updated this PR after the review. |
Craigacp
added a commit
that referenced
this pull request
Dec 22, 2024
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
Adds a Gaussian Mixture Model clustering implementation with spherical, diagonal and full covariance structure using Expectation Maximisation. Also adds a mixture distribution to the RNG library to allow sampling from a user constructed gaussian mixture model (as opposed to one fit to a data distribution).
It also contains new Math functions necessary to implement the GMM efficiently, some updates for K-Means to modernise it a little bit, and some cleanups to the main pom file.
There are a few important fixes to the Math package in here as well, determinants for matrix factorizations were incorrectly computed, and the subtract function on SparseVector was incorrect.
Motivation
GMMs are a useful clustering algorithm. Fixes #359.
Paper reference
Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition.