Module: Rumale

Defined in:

lib/rumale/version.rb,
lib/rumale/utils.rb,
lib/rumale/values.rb,
lib/rumale/dataset.rb,
lib/rumale/tree/node.rb,
lib/rumale/validation.rb,
lib/rumale/base/splitter.rb,
lib/rumale/manifold/tsne.rb,
lib/rumale/optimizer/sgd.rb,
lib/rumale/base/evaluator.rb,
lib/rumale/base/regressor.rb,
lib/rumale/optimizer/adam.rb,
lib/rumale/base/classifier.rb,
lib/rumale/optimizer/nadam.rb,
lib/rumale/pairwise_metric.rb,
lib/rumale/base/transformer.rb,
lib/rumale/linear_model/svc.rb,
lib/rumale/linear_model/svr.rb,
lib/rumale/clustering/dbscan.rb,
lib/rumale/decomposition/nmf.rb,
lib/rumale/decomposition/pca.rb,
lib/rumale/optimizer/rmsprop.rb,
lib/rumale/pipeline/pipeline.rb,
lib/rumale/clustering/k_means.rb,
lib/rumale/linear_model/lasso.rb,
lib/rumale/linear_model/ridge.rb,
lib/rumale/optimizer/ada_grad.rb,
lib/rumale/base/base_estimator.rb,
lib/rumale/optimizer/yellow_fin.rb,
lib/rumale/probabilistic_output.rb,
lib/rumale/base/cluster_analyzer.rb,
lib/rumale/model_selection/k_fold.rb,
lib/rumale/naive_bayes/naive_bayes.rb,
lib/rumale/tree/base_decision_tree.rb,
lib/rumale/kernel_approximation/rbf.rb,
lib/rumale/evaluation_measure/purity.rb,
lib/rumale/evaluation_measure/recall.rb,
lib/rumale/kernel_machine/kernel_svc.rb,
lib/rumale/tree/extra_tree_regressor.rb,
lib/rumale/evaluation_measure/f_score.rb,
lib/rumale/evaluation_measure/roc_auc.rb,
lib/rumale/tree/extra_tree_classifier.rb,
lib/rumale/evaluation_measure/accuracy.rb,
lib/rumale/evaluation_measure/log_loss.rb,
lib/rumale/evaluation_measure/r2_score.rb,
lib/rumale/preprocessing/l2_normalizer.rb,
lib/rumale/preprocessing/label_encoder.rb,
lib/rumale/ensemble/ada_boost_regressor.rb,
lib/rumale/evaluation_measure/precision.rb,
lib/rumale/preprocessing/max_abs_scaler.rb,
lib/rumale/preprocessing/min_max_scaler.rb,
lib/rumale/tree/decision_tree_regressor.rb,
lib/rumale/tree/gradient_tree_regressor.rb,
lib/rumale/ensemble/ada_boost_classifier.rb,
lib/rumale/model_selection/shuffle_split.rb,
lib/rumale/preprocessing/bin_discretizer.rb,
lib/rumale/preprocessing/one_hot_encoder.rb,
lib/rumale/preprocessing/standard_scaler.rb,
lib/rumale/tree/decision_tree_classifier.rb,
lib/rumale/ensemble/extra_trees_regressor.rb,
lib/rumale/linear_model/base_linear_model.rb,
lib/rumale/linear_model/linear_regression.rb,
lib/rumale/model_selection/grid_search_cv.rb,
lib/rumale/ensemble/extra_trees_classifier.rb,
lib/rumale/ensemble/random_forest_regressor.rb,
lib/rumale/linear_model/logistic_regression.rb,
lib/rumale/model_selection/cross_validation.rb,
lib/rumale/ensemble/random_forest_classifier.rb,
lib/rumale/model_selection/stratified_k_fold.rb,
lib/rumale/multiclass/one_vs_rest_classifier.rb,
lib/rumale/evaluation_measure/precision_recall.rb,
lib/rumale/ensemble/gradient_boosting_regressor.rb,
lib/rumale/ensemble/gradient_boosting_classifier.rb,
lib/rumale/evaluation_measure/mean_squared_error.rb,
lib/rumale/evaluation_measure/mutual_information.rb,
lib/rumale/evaluation_measure/adjusted_rand_score.rb,
lib/rumale/evaluation_measure/mean_absolute_error.rb,
lib/rumale/nearest_neighbors/k_neighbors_regressor.rb,
lib/rumale/evaluation_measure/median_absolute_error.rb,
lib/rumale/model_selection/stratified_shuffle_split.rb,
lib/rumale/nearest_neighbors/k_neighbors_classifier.rb,
lib/rumale/evaluation_measure/mean_squared_log_error.rb,
lib/rumale/evaluation_measure/explained_variance_score.rb,
lib/rumale/polynomial_model/base_factorization_machine.rb,
lib/rumale/evaluation_measure/normalized_mutual_information.rb,
lib/rumale/polynomial_model/factorization_machine_regressor.rb,
lib/rumale/polynomial_model/factorization_machine_classifier.rb,
ext/rumale/rumale.c

Overview

Rumale is a machine learning library in Ruby.

Defined Under Namespace

Modules: Base, Clustering, Dataset, Decomposition, Ensemble, EvaluationMeasure, KernelApproximation, KernelMachine, LinearModel, Manifold, ModelSelection, Multiclass, NaiveBayes, NearestNeighbors, Optimizer, PairwiseMetric, Pipeline, PolynomialModel, Preprocessing, ProbabilisticOutput, Tree

Constant Summary

VERSION =

The version of Rumale you are using.

'0.10.0'