30 packages found

Rumale::NaiveBayes provides naive bayes models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, and Bernoulli Naive Bayes, with Rumale interface.

pycall

Rumale is a machine learning library in Ruby. Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. Rumale supports Support Vector Machine, Logistic Regression, Ridge, Lasso, Multi-layer Perceptron, Naive Bayes, Decision Tree, Gradient Tree Boosting, Random Forest, K-Means, Gaussian Mixture Model, DBSCAN, Spectral Clustering, Mutidimensional Scaling, t-SNE, Fisher Discriminant Analysis, Neighbourhood Component Analysis, Principal Component Analysis,…

Rumale::NeuralNetwork provides classifiers and regression algorithms based on multi-layer perceptron, radial basis function network, and random vector functional link network in the Rumale interface.

Rumale::KernelApproximation provides kernel approximation algorithms, such as RBF feature mapping and Nystroem method, with Rumale interface.

Rumale::Preprocessing provides preprocessing techniques, such as L2 normalization, standard scaling, and one-hot encoding, with Rumale interface.

Rumale::MetricLearning provides metric learning algorithms, such as Fisher Discriminant Analysis and Neighboourhood Component Analysis with Rumale interface.

Rumale::Tree provides classifier and regression based on decision tree algorithms with Rumale interface.

ID3-based implementation of the M.L. Decision Tree algorithm

Rumale::Manifold provides data embedding algorithms, such as Multi-dimensional Scaling, Locally Linear Embedding, Laplacian Eigenmaps, Hessian Eigenmaps, and t-distributed Stochastic Neighbor Embedding, with Rumale interface.