Module: Rumale::Base::BaseEstimator

Included in:
Clustering::DBSCAN, Clustering::GaussianMixture, Clustering::HDBSCAN, Clustering::KMeans, Clustering::KMedoids, Clustering::MiniBatchKMeans, Clustering::PowerIteration, Clustering::SingleLinkage, Clustering::SpectralClustering, Decomposition::FactorAnalysis, Decomposition::FastICA, Decomposition::NMF, Decomposition::PCA, Ensemble::AdaBoostClassifier, Ensemble::AdaBoostRegressor, Ensemble::GradientBoostingClassifier, Ensemble::GradientBoostingRegressor, Ensemble::RandomForestClassifier, Ensemble::RandomForestRegressor, Ensemble::StackingClassifier, Ensemble::StackingRegressor, Ensemble::VotingClassifier, Ensemble::VotingRegressor, FeatureExtraction::FeatureHasher, FeatureExtraction::HashVectorizer, FeatureExtraction::TfidfTransformer, KernelApproximation::Nystroem, KernelApproximation::RBF, KernelMachine::KernelFDA, KernelMachine::KernelPCA, KernelMachine::KernelRidge, KernelMachine::KernelRidgeClassifier, KernelMachine::KernelSVC, LinearModel::BaseSGD, LinearModel::NNLS, Manifold::MDS, Manifold::TSNE, MetricLearning::FisherDiscriminantAnalysis, MetricLearning::MLKR, MetricLearning::NeighbourhoodComponentAnalysis, ModelSelection::GridSearchCV, Multiclass::OneVsRestClassifier, NaiveBayes::BaseNaiveBayes, NearestNeighbors::KNeighborsClassifier, NearestNeighbors::KNeighborsRegressor, NearestNeighbors::VPTree, NeuralNetwork::BaseMLP, Pipeline::FeatureUnion, Pipeline::Pipeline, Preprocessing::BinDiscretizer, Preprocessing::Binarizer, Preprocessing::KernelCalculator, Preprocessing::L1Normalizer, Preprocessing::L2Normalizer, Preprocessing::LabelBinarizer, Preprocessing::LabelEncoder, Preprocessing::MaxAbsScaler, Preprocessing::MaxNormalizer, Preprocessing::MinMaxScaler, Preprocessing::OneHotEncoder, Preprocessing::OrdinalEncoder, Preprocessing::PolynomialFeatures, Preprocessing::StandardScaler, Tree::BaseDecisionTree, Tree::GradientTreeRegressor
Defined in:
lib/rumale/base/base_estimator.rb

Overview

Base module for all estimators in Rumale.

Instance Attribute Summary collapse

Instance Attribute Details

#paramsHash (readonly)

Return parameters about an estimator.

Returns:

  • (Hash)


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# File 'lib/rumale/base/base_estimator.rb', line 10

def params
  @params
end