40 REQUIRE(gradient_updater,
"Gradient updater must set\n");
57 REQUIRE(num_passes>0,
"The number (%d) to go through data must be positive\n", num_passes);
95 void FirstOrderStochasticMinimizer::init()
DescendUpdater * m_gradient_updater
virtual void set_learning_rate(LearningRate *learning_rate)
The base class about learning rate for descent-based minimizers.
float64_t m_penalty_weight
virtual void init_minimization()
FirstOrderCostFunction * m_fun
The base class for sparse penalty/regularization used in minimization.
The base class for sparse penalty/regularization used in minimization.
Class SGObject is the base class of all shogun objects.
LearningRate * m_learning_rate
virtual void set_number_passes(int32_t num_passes)
virtual void update_variable_for_proximity(SGVector< float64_t > variable, float64_t proximal_weight)=0
virtual void do_proximal_operation(SGVector< float64_t >variable_reference)
virtual void set_gradient_updater(DescendUpdater *gradient_updater)
This is a base class for descend update.
virtual ~FirstOrderStochasticMinimizer()
all of classes and functions are contained in the shogun namespace
virtual float64_t get_learning_rate(int32_t iter_counter)=0