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growing_inputs.h
Go to the documentation of this file.
InputsSelectionResults perform_input_selection() override
Runs the greedy input growing procedure until the stopping criterion is met.
void set_minimum_correlation(const float)
Sets the minimum correlation an input must have with the targets to be considered.
void set_minimum_inputs_number(const Index)
Sets the lower bound on the number of inputs that may be selected.
void set_maximum_correlation(const float)
Sets the maximum allowed correlation between selected inputs.
void to_JSON(JsonWriter &) const override
Writes algorithm configuration to a JSON writer.
void set_default()
Restores default bounds, correlation thresholds and stopping criteria.
Index get_maximum_inputs_number() const override
Returns the maximum number of inputs the algorithm is allowed to select.
GrowingInputs(TrainingStrategy *=nullptr)
Constructs the algorithm bound to an optional training strategy.
Index get_minimum_inputs_number() const override
Returns the minimum number of inputs the algorithm is allowed to select.
void from_JSON(const JsonDocument &) override
Loads algorithm configuration from a JSON document.
void set_maximum_inputs_number(const Index)
Sets the upper bound on the number of inputs that may be selected.
InputsSelection(TrainingStrategy *=nullptr)
Constructs the algorithm bound to an optional training strategy.
Definition json.h:72
Definition json.h:85
High-level orchestrator pairing a Loss with an Optimizer for a network/dataset.
Definition training_strategy.h:24
Definition adaptive_moment_estimation.h:14
Aggregated results of an inputs selection run including optimal inputs and error histories.
Definition inputs_selection.h:112