Class: Rumale::LinearModel::BaseLinearModel

Inherits:
Object
  • Object
show all
Includes:
Base::BaseEstimator
Defined in:
lib/rumale/linear_model/base_linear_model.rb

Overview

BaseLinearModel is an abstract class for implementation of linear estimator with mini-batch stochastic gradient descent optimization. This class is used for internal process.

Direct Known Subclasses

Lasso, LinearRegression, LogisticRegression, Ridge, SVC, SVR

Instance Attribute Summary

Attributes included from Base::BaseEstimator

#params

Instance Method Summary collapse

Constructor Details

#initialize(reg_param: 1.0, fit_bias: false, bias_scale: 1.0, max_iter: 1000, batch_size: 10, optimizer: nil, n_jobs: nil, random_seed: nil) ⇒ BaseLinearModel

Initialize a linear estimator.



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# File 'lib/rumale/linear_model/base_linear_model.rb', line 27

def initialize(reg_param: 1.0, fit_bias: false, bias_scale: 1.0,
               max_iter: 1000, batch_size: 10, optimizer: nil, n_jobs: nil, random_seed: nil)
  @params = {}
  @params[:reg_param] = reg_param
  @params[:fit_bias] = fit_bias
  @params[:bias_scale] = bias_scale
  @params[:max_iter] = max_iter
  @params[:batch_size] = batch_size
  @params[:optimizer] = optimizer
  @params[:optimizer] ||= Optimizer::Nadam.new
  @params[:n_jobs] = n_jobs
  @params[:random_seed] = random_seed
  @params[:random_seed] ||= srand
  @weight_vec = nil
  @bias_term = nil
  @rng = Random.new(@params[:random_seed])
end