Class: Rumale::PolynomialModel::BaseFactorizationMachine

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

Overview

BaseFactorizationMachine is an abstract class for implementation of Factorization Machine-based estimators. This class is used internally.

Instance Attribute Summary

Attributes included from Base::BaseEstimator

#params

Instance Method Summary collapse

Constructor Details

#initialize(n_factors: 2, loss: nil, reg_param_linear: 1.0, reg_param_factor: 1.0, max_iter: 1000, batch_size: 10, optimizer: nil, random_seed: nil) ⇒ BaseFactorizationMachine

Initialize a Factorization Machine-based estimator.

Parameters:

  • n_factors (Integer) (defaults to: 2) —

    The maximum number of iterations.

  • loss (String) (defaults to: nil) —

    The loss function (‘hinge’ or ‘logistic’ or nil).

  • reg_param_linear (Float) (defaults to: 1.0) —

    The regularization parameter for linear model.

  • reg_param_factor (Float) (defaults to: 1.0) —

    The regularization parameter for factor matrix.

  • max_iter (Integer) (defaults to: 1000) —

    The maximum number of iterations.

  • batch_size (Integer) (defaults to: 10) —

    The size of the mini batches.

  • optimizer (Optimizer) (defaults to: nil) —

    The optimizer to calculate adaptive learning rate. If nil is given, Nadam is used.

  • random_seed (Integer) (defaults to: nil) —

    The seed value using to initialize the random generator.



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# File 'lib/rumale/polynomial_model/base_factorization_machine.rb', line 25

def initialize(n_factors: 2, loss: nil, reg_param_linear: 1.0, reg_param_factor: 1.0,
               max_iter: 1000, batch_size: 10, optimizer: nil, random_seed: nil)
  @params = {}
  @params[:n_factors] = n_factors
  @params[:loss] = loss unless loss.nil?
  @params[:reg_param_linear] = reg_param_linear
  @params[:reg_param_factor] = reg_param_factor
  @params[:max_iter] = max_iter
  @params[:batch_size] = batch_size
  @params[:optimizer] = optimizer
  @params[:optimizer] ||= Optimizer::Nadam.new
  @params[:random_seed] = random_seed
  @params[:random_seed] ||= srand
  @factor_mat = nil
  @weight_vec = nil
  @bias_term = nil
  @rng = Random.new(@params[:random_seed])
end