Module: SVMKit::Base::BaseEstimator

Included in:
Ensemble::RandomForestClassifier, Ensemble::RandomForestRegressor, KernelApproximation::RBF, KernelMachine::KernelSVC, LinearModel::Lasso, LinearModel::LinearRegression, LinearModel::LogisticRegression, LinearModel::Ridge, LinearModel::SVC, LinearModel::SVR, Multiclass::OneVsRestClassifier, NaiveBayes::BaseNaiveBayes, NearestNeighbors::KNeighborsClassifier, NearestNeighbors::KNeighborsRegressor, Optimizer::Nadam, Optimizer::RMSProp, Optimizer::SGD, Optimizer::YellowFin, PolynomialModel::FactorizationMachineClassifier, PolynomialModel::FactorizationMachineRegressor, Preprocessing::L2Normalizer, Preprocessing::LabelEncoder, Preprocessing::MinMaxScaler, Preprocessing::OneHotEncoder, Preprocessing::StandardScaler, Tree::DecisionTreeClassifier, Tree::DecisionTreeRegressor
Defined in:
lib/svmkit/base/base_estimator.rb

Overview

Base module for all estimators in SVMKit.

Instance Attribute Summary collapse

Instance Attribute Details

#params ⇒ Hash (readonly)

Return parameters about an estimator.

Returns:

  • (Hash) 


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

def params
  @params
end