jonghough/jlearn

Machine Learning Library, written in J

31 commits

updated Nov 29, 2023

README

        _____   _____     ________       _       _______     ____  _____  
       |_   _| |_   _|   |_   __  |     / \     |_   __ \   |_   \|_   _| 
         | |     | |       | |_ \_|    / _ \      | |__) |    |   \ | |   
     _   | |     | |   _   |  _| _    / ___ \     |  __ /     | |\ \| |   
    | |__' | _  _| |__/ | _| |__/ | _/ /   \ \_  _| |  \ \_  _| |_\   |_  
    `.____.'(_)|________||________||____| |____||____| |___||_____|\____|

brain

Machine Learning with J.

WIP Machine learning library, written in J. Various algorithm implementations, including MLPClassifiers, MLPRegressors, Mixture Models, K-Means, KNN, RBF-Network, Self-organizing Maps.

som_clusters

Implemented Algorithms

Algorithm	Classification	Regression	Clustering	Pattern Matching / Completion	Other	Notes
Multilayer Perceptron	o	o	n/a	n/a		Batch SGD with choice of gradient optimizers.
Gaussian Processes	x	o	n/a	n/a
RBF Network	o	o	n/a	n/a
Decision Tree	o	x	n/a	n/a		Regressor needs implementing.
AdaBoost Ensemble	o	x	n/a	n/a
Gaussian Mixtures	n/a	n/a	o	n/a
K-means / K-medians	n/a	n/a	o	n/a
Hierarchical Clustering	n/a	n/a	o	n/a		Agglomerative clustering
K-nearest Neighbours	n/a	n/a	o	n/a
DBSCAN	n/a	n/a	o	n/a
Kd-tree	o	x	o	n/a
Self-Organizing Maps	n/a	n/a	n/a	o
Hopfield Networks	n/a	x	n/a	o
Restricted Boltzmann Machines	o	n/a	n/a	o		Partial implementation.
Convolutional Neural Networks	o	n/a	n/a	n/a		Experimental. 2D convolutions implemented.
Recurrent Neural Networks	o	x	n/a	n/a		Experimental. LSTMs implemented.
PCA / KPCA	n/a	n/a	n/a	n/a	o	Dimensionality reduction.
Genetic Algorithm Solver	n/a	n/a	n/a	n/a	o	Optimization.
Symbolic Regression Solver	n/a	n/a	n/a	n/a	o	Function estimation.

Other features

Serialization

Models can be serialized to text files, with a mixture of text and binary packing. The size of the serialized file depends on the size of the model, but will probably range from 10 MB and upwards for NN models (including convnets and rec-nets).

clustering

convolutional-neural-networks

deep-learning

ensemble-learning

gaussian-mixture-models

gaussian-processes

hierarchical-clustering

k-means

knn-classifier

learning

lstm

machine-learning

multilayer-perceptron-network

principal-component-analysis

rbm

restricted-boltzmann-machines

self-organizing-map

Contributors

jonghough

31 commits

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jonghough/jlearn

Machine Learning Library, written in J

31 commits

updated Nov 29, 2023

See the code

README

        _____   _____     ________       _       _______     ____  _____  
       |_   _| |_   _|   |_   __  |     / \     |_   __ \   |_   \|_   _| 
         | |     | |       | |_ \_|    / _ \      | |__) |    |   \ | |   
     _   | |     | |   _   |  _| _    / ___ \     |  __ /     | |\ \| |   
    | |__' | _  _| |__/ | _| |__/ | _/ /   \ \_  _| |  \ \_  _| |_\   |_  
    `.____.'(_)|________||________||____| |____||____| |___||_____|\____|

brain

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som_clusters

Implemented Algorithms

Algorithm	Classification	Regression	Clustering	Pattern Matching / Completion	Other	Notes
Multilayer Perceptron	o	o	n/a	n/a		Batch SGD with choice of gradient optimizers.
Gaussian Processes	x	o	n/a	n/a
RBF Network	o	o	n/a	n/a
Decision Tree	o	x	n/a	n/a		Regressor needs implementing.
AdaBoost Ensemble	o	x	n/a	n/a
Gaussian Mixtures	n/a	n/a	o	n/a
K-means / K-medians	n/a	n/a	o	n/a
Hierarchical Clustering	n/a	n/a	o	n/a		Agglomerative clustering
K-nearest Neighbours	n/a	n/a	o	n/a
DBSCAN	n/a	n/a	o	n/a
Kd-tree	o	x	o	n/a
Self-Organizing Maps	n/a	n/a	n/a	o
Hopfield Networks	n/a	x	n/a	o
Restricted Boltzmann Machines	o	n/a	n/a	o		Partial implementation.
Convolutional Neural Networks	o	n/a	n/a	n/a		Experimental. 2D convolutions implemented.
Recurrent Neural Networks	o	x	n/a	n/a		Experimental. LSTMs implemented.
PCA / KPCA	n/a	n/a	n/a	n/a	o	Dimensionality reduction.
Genetic Algorithm Solver	n/a	n/a	n/a	n/a	o	Optimization.
Symbolic Regression Solver	n/a	n/a	n/a	n/a	o	Function estimation.

Other features

Serialization

clustering

convolutional-neural-networks

deep-learning

ensemble-learning

gaussian-mixture-models

gaussian-processes

hierarchical-clustering

k-means

knn-classifier

learning

lstm

machine-learning

multilayer-perceptron-network

principal-component-analysis

rbm

restricted-boltzmann-machines

self-organizing-map

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