Module: Rumale::Base::BaseEstimator

Included in:
Clustering::DBSCAN, Clustering::GaussianMixture, Clustering::KMeans, Clustering::KMedoids, Clustering::PowerIteration, Decomposition::NMF, Decomposition::PCA, Ensemble::AdaBoostClassifier, Ensemble::AdaBoostRegressor, Ensemble::GradientBoostingClassifier, Ensemble::GradientBoostingRegressor, Ensemble::RandomForestClassifier, Ensemble::RandomForestRegressor, KernelApproximation::RBF, KernelMachine::KernelSVC, LinearModel::BaseLinearModel, Manifold::MDS, Manifold::TSNE, ModelSelection::GridSearchCV, Multiclass::OneVsRestClassifier, NaiveBayes::BaseNaiveBayes, NearestNeighbors::KNeighborsClassifier, NearestNeighbors::KNeighborsRegressor, Optimizer::AdaGrad, Optimizer::Adam, Optimizer::Nadam, Optimizer::RMSProp, Optimizer::SGD, Optimizer::YellowFin, Pipeline::Pipeline, PolynomialModel::BaseFactorizationMachine, Preprocessing::BinDiscretizer, Preprocessing::L2Normalizer, Preprocessing::LabelEncoder, Preprocessing::MaxAbsScaler, Preprocessing::MinMaxScaler, Preprocessing::OneHotEncoder, Preprocessing::OrdinalEncoder, 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

#params ⇒ Hash (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