# -*- encoding: utf-8 -*-
# stub: svmkit 0.7.3 ruby lib

Gem::Specification.new do |s|
  s.name = "svmkit".freeze
  s.version = "0.7.3".freeze

  s.required_rubygems_version = Gem::Requirement.new(">= 0".freeze) if s.respond_to? :required_rubygems_version=
  s.require_paths = ["lib".freeze]
  s.authors = ["yoshoku".freeze]
  s.bindir = "exe".freeze
  s.date = "2019-02-05"
  s.description = "SVMKit is a machine learninig library in Ruby.\nSVMKit provides machine learning algorithms with interfaces similar to Scikit-Learn in Python.\nSVMKit currently supports Linear / Kernel Support Vector Machine,\nLogistic Regression, Linear Regression, Ridge, Lasso, Factorization Machine,\nNaive Bayes, Decision Tree, AdaBoost, Random Forest, K-nearest neighbor algorithm,\nK-Means, DBSCAN, Principal Component Analysis, Non-negative Matrix Factorization\nand cross-validation.\n".freeze
  s.email = ["yoshoku@outlook.com".freeze]
  s.files = [".coveralls.yml".freeze, ".gitignore".freeze, ".rspec".freeze, ".rubocop.yml".freeze, ".rubocop_todo.yml".freeze, ".travis.yml".freeze, "CODE_OF_CONDUCT.md".freeze, "Gemfile".freeze, "HISTORY.md".freeze, "LICENSE.txt".freeze, "README.md".freeze, "Rakefile".freeze, "bin/console".freeze, "bin/setup".freeze, "lib/svmkit.rb".freeze, "lib/svmkit/base/base_estimator.rb".freeze, "lib/svmkit/base/classifier.rb".freeze, "lib/svmkit/base/cluster_analyzer.rb".freeze, "lib/svmkit/base/evaluator.rb".freeze, "lib/svmkit/base/regressor.rb".freeze, "lib/svmkit/base/splitter.rb".freeze, "lib/svmkit/base/transformer.rb".freeze, "lib/svmkit/clustering/dbscan.rb".freeze, "lib/svmkit/clustering/k_means.rb".freeze, "lib/svmkit/dataset.rb".freeze, "lib/svmkit/decomposition/nmf.rb".freeze, "lib/svmkit/decomposition/pca.rb".freeze, "lib/svmkit/ensemble/ada_boost_classifier.rb".freeze, "lib/svmkit/ensemble/ada_boost_regressor.rb".freeze, "lib/svmkit/ensemble/random_forest_classifier.rb".freeze, "lib/svmkit/ensemble/random_forest_regressor.rb".freeze, "lib/svmkit/evaluation_measure/accuracy.rb".freeze, "lib/svmkit/evaluation_measure/f_score.rb".freeze, "lib/svmkit/evaluation_measure/log_loss.rb".freeze, "lib/svmkit/evaluation_measure/mean_absolute_error.rb".freeze, "lib/svmkit/evaluation_measure/mean_squared_error.rb".freeze, "lib/svmkit/evaluation_measure/normalized_mutual_information.rb".freeze, "lib/svmkit/evaluation_measure/precision.rb".freeze, "lib/svmkit/evaluation_measure/precision_recall.rb".freeze, "lib/svmkit/evaluation_measure/purity.rb".freeze, "lib/svmkit/evaluation_measure/r2_score.rb".freeze, "lib/svmkit/evaluation_measure/recall.rb".freeze, "lib/svmkit/kernel_approximation/rbf.rb".freeze, "lib/svmkit/kernel_machine/kernel_svc.rb".freeze, "lib/svmkit/linear_model/lasso.rb".freeze, "lib/svmkit/linear_model/linear_regression.rb".freeze, "lib/svmkit/linear_model/logistic_regression.rb".freeze, "lib/svmkit/linear_model/ridge.rb".freeze, "lib/svmkit/linear_model/sgd_linear_estimator.rb".freeze, "lib/svmkit/linear_model/svc.rb".freeze, "lib/svmkit/linear_model/svr.rb".freeze, "lib/svmkit/model_selection/cross_validation.rb".freeze, "lib/svmkit/model_selection/grid_search_cv.rb".freeze, "lib/svmkit/model_selection/k_fold.rb".freeze, "lib/svmkit/model_selection/stratified_k_fold.rb".freeze, "lib/svmkit/multiclass/one_vs_rest_classifier.rb".freeze, "lib/svmkit/naive_bayes/naive_bayes.rb".freeze, "lib/svmkit/nearest_neighbors/k_neighbors_classifier.rb".freeze, "lib/svmkit/nearest_neighbors/k_neighbors_regressor.rb".freeze, "lib/svmkit/optimizer/nadam.rb".freeze, "lib/svmkit/optimizer/rmsprop.rb".freeze, "lib/svmkit/optimizer/sgd.rb".freeze, "lib/svmkit/optimizer/yellow_fin.rb".freeze, "lib/svmkit/pairwise_metric.rb".freeze, "lib/svmkit/pipeline/pipeline.rb".freeze, "lib/svmkit/polynomial_model/factorization_machine_classifier.rb".freeze, "lib/svmkit/polynomial_model/factorization_machine_regressor.rb".freeze, "lib/svmkit/preprocessing/l2_normalizer.rb".freeze, "lib/svmkit/preprocessing/label_encoder.rb".freeze, "lib/svmkit/preprocessing/min_max_scaler.rb".freeze, "lib/svmkit/preprocessing/one_hot_encoder.rb".freeze, "lib/svmkit/preprocessing/standard_scaler.rb".freeze, "lib/svmkit/probabilistic_output.rb".freeze, "lib/svmkit/tree/decision_tree_classifier.rb".freeze, "lib/svmkit/tree/decision_tree_regressor.rb".freeze, "lib/svmkit/tree/node.rb".freeze, "lib/svmkit/utils.rb".freeze, "lib/svmkit/validation.rb".freeze, "lib/svmkit/values.rb".freeze, "lib/svmkit/version.rb".freeze, "svmkit.gemspec".freeze]
  s.homepage = "https://github.com/yoshoku/svmkit".freeze
  s.licenses = ["BSD-2-Clause".freeze]
  s.required_ruby_version = Gem::Requirement.new(">= 2.1".freeze)
  s.rubygems_version = "3.5.10".freeze
  s.summary = "SVMKit is a machine learninig library in Ruby. SVMKit provides machine learning algorithms with interfaces similar to Scikit-Learn in Python.".freeze

  s.specification_version = 4

  s.add_runtime_dependency(%q<numo-narray>.freeze, [">= 0.9.1".freeze])
  s.add_development_dependency(%q<bundler>.freeze, [">= 1.16".freeze])
  s.add_development_dependency(%q<coveralls>.freeze, ["~> 0.8".freeze])
  s.add_development_dependency(%q<rake>.freeze, ["~> 12.0".freeze])
  s.add_development_dependency(%q<rspec>.freeze, ["~> 3.0".freeze])
end