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This concrete class represents a growing inputs algorithm for the InputsSelection as part of the ModelSelection[1] class. More...
#include <growing_inputs.h>
Public Member Functions | |
| GrowingInputs () | |
| Default constructor. More... | |
| GrowingInputs (TrainingStrategy *) | |
| virtual | ~GrowingInputs () |
| Destructor. More... | |
| const Index & | get_maximum_inputs_number () const |
| Returns the maximum number of inputs in the growing inputs selection algorithm. More... | |
| const Index & | get_minimum_inputs_number () const |
| Returns the minimum number of inputs in the growing inputs selection algorithm. More... | |
| const Index & | get_maximum_selection_failures () const |
| Returns the maximum number of selection failures in the growing inputs selection algorithm. More... | |
| void | set_default () |
| Sets the members of the growing inputs object to their default values. More... | |
| void | set_maximum_inputs_number (const Index &) |
| void | set_minimum_inputs_number (const Index &) |
| void | set_maximum_selection_failures (const Index &) |
| InputsSelectionResults | perform_inputs_selection () |
| Perform inputs selection with the growing inputs method. More... | |
| Tensor< string, 2 > | to_string_matrix () const |
| Writes as matrix of strings the most representative atributes. More... | |
| void | from_XML (const tinyxml2::XMLDocument &) |
| void | write_XML (tinyxml2::XMLPrinter &) const |
| void | save (const string &) const |
| void | load (const string &) |
 Public Member Functions inherited from InputsSelection | |
| InputsSelection () | |
| Default constructor. More... | |
| InputsSelection (TrainingStrategy *) | |
| virtual | ~InputsSelection () |
| Destructor. More... | |
| TrainingStrategy * | get_training_strategy_pointer () const |
| Returns a pointer to the training strategy object. More... | |
| bool | has_training_strategy () const |
| Returns true if this inputs selection algorithm has a training strategy associated, and false otherwise. More... | |
| const Index & | get_trials_number () const |
| Returns the number of trials for each network architecture. More... | |
| const bool & | get_display () const |
| const type & | get_selection_error_goal () const |
| Returns the goal for the selection error in the inputs selection algorithm. More... | |
| const Index & | get_maximum_iterations_number () const |
| Returns the maximum number of iterations in the inputs selection algorithm. More... | |
| const type & | get_maximum_time () const |
| Returns the maximum time in the inputs selection algorithm. More... | |
| const type & | get_maximum_correlation () const |
| Return the maximum correlation for the algorithm. More... | |
| const type & | get_minimum_correlation () const |
| Return the minimum correlation for the algorithm. More... | |
| const type & | get_tolerance () const |
| void | set (TrainingStrategy *) |
| void | set_default () |
| Sets the members of the inputs selection object to their default values. More... | |
| void | set_trials_number (const Index &) |
| void | set_display (const bool &) |
| void | set_selection_error_goal (const type &) |
| void | set_maximum_epochs_number (const Index &) |
| void | set_maximum_time (const type &) |
| void | set_maximum_correlation (const type &) |
| void | set_minimum_correlation (const type &) |
| string | write_stopping_condition (const TrainingResults &) const |
| void | check () const |
| Checks that the different pointers needed for performing the inputs selection are not nullptr. More... | |
| Index | get_input_index (const Tensor< DataSet::VariableUse, 1 > &, const Index &) |
| const string | write_time (const type &) const |
| Writes the time from seconds in format HH:mm:ss. More... | |
Private Attributes | |
| Index | maximum_inputs_number |
| Maximum number of inputs in the neural network. More... | |
| Index | minimum_inputs_number = 1 |
| Minimum number of inputs in the neural network. More... | |
| Index | maximum_selection_failures = 100 |
| Maximum number of epochs at which the selection error increases. More... | |
Additional Inherited Members | |
| Public Types inherited from InputsSelection | |
| enum class | StoppingCondition { MaximumTime , SelectionErrorGoal , MaximumInputs , MinimumInputs , MaximumEpochs , MaximumSelectionFailures , CorrelationGoal } |
| Enumeration of all possibles condition of stop for the algorithms. More... | |
| Protected Attributes inherited from InputsSelection | |
| TrainingStrategy * | training_strategy_pointer = nullptr |
| Pointer to a training strategy object. More... | |
| Tensor< Index, 1 > | original_input_columns_indices |
| Tensor< Index, 1 > | original_target_columns_indices |
| Index | trials_number = 1 |
| Number of trials for each neural network. More... | |
| bool | display = true |
| Display messages to screen. More... | |
| type | selection_error_goal |
| Goal value for the selection error. It is used as a stopping criterion. More... | |
| Index | maximum_epochs_number |
| Maximum number of epochs to perform_inputs_selection. It is used as a stopping criterion. More... | |
| type | maximum_correlation |
| Maximum value for the correlations. More... | |
| type | minimum_correlation |
| Minimum value for the correlations. More... | |
| type | maximum_time |
| Maximum selection algorithm time. It is used as a stopping criterion. More... | |
| const Eigen::array< int, 1 > | rows_sum = {Eigen::array<int, 1>({1})} |
This concrete class represents a growing inputs algorithm for the InputsSelection as part of the ModelSelection[1] class.
[1] Neural Designer "Model Selection Algorithms in Predictive Analytics." https://www.neuraldesigner.com/blog/model-selection
Definition at line 36 of file growing_inputs.h.
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explicit |
Default constructor.
Definition at line 16 of file growing_inputs.cpp.
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explicit |
Training strategy constructor.
| new_training_strategy_pointer | Pointer to a training strategy object. |
Definition at line 26 of file growing_inputs.cpp.
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Destructor.
Definition at line 35 of file growing_inputs.cpp.
| void from_XML | ( | const tinyxml2::XMLDocument & | document | ) |
Deserializes a TinyXML document into this growing inputs object.
| document | TinyXML document containing the member data. |
Definition at line 602 of file growing_inputs.cpp.
| const Index & get_maximum_inputs_number | ( | ) | const |
Returns the maximum number of inputs in the growing inputs selection algorithm.
Definition at line 42 of file growing_inputs.cpp.
| const Index & get_maximum_selection_failures | ( | ) | const |
Returns the maximum number of selection failures in the growing inputs selection algorithm.
Definition at line 58 of file growing_inputs.cpp.
| const Index & get_minimum_inputs_number | ( | ) | const |
Returns the minimum number of inputs in the growing inputs selection algorithm.
Definition at line 50 of file growing_inputs.cpp.
| void load | ( | const string & | file_name | ) |
Loads a growing inputs object from a XML-type file.
| file_name | Name of growing inputs XML-type file. |
Definition at line 830 of file growing_inputs.cpp.
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Perform inputs selection with the growing inputs method.
Implements InputsSelection.
Definition at line 171 of file growing_inputs.cpp.
| void save | ( | const string & | file_name | ) | const |
Saves to a XML-type file the members of the growing inputs object.
| file_name | Name of growing inputs XML-type file. |
Definition at line 815 of file growing_inputs.cpp.
| void set_default | ( | ) |
Sets the members of the growing inputs object to their default values.
Definition at line 66 of file growing_inputs.cpp.
| void set_maximum_inputs_number | ( | const Index & | new_maximum_inputs_number | ) |
Sets the maximum inputs number for the growing inputs selection algorithm.
| new_maximum_inputs_number | Maximum inputs number in the growing inputs selection algorithm. |
Definition at line 100 of file growing_inputs.cpp.
| void set_maximum_selection_failures | ( | const Index & | new_maximum_selection_failures | ) |
Sets the maximum selection failures for the growing inputs selection algorithm.
| new_maximum_selection_failures | Maximum number of selection failures in the growing inputs selection algorithm. |
Definition at line 148 of file growing_inputs.cpp.
| void set_minimum_inputs_number | ( | const Index & | new_minimum_inputs_number | ) |
Sets the minimum inputs number for the growing inputs selection algorithm.
| new_minimum_inputs_number | Minimum inputs number in the growing inputs selection algorithm. |
Definition at line 124 of file growing_inputs.cpp.
| Tensor< string, 2 > to_string_matrix | ( | ) | const |
Writes as matrix of strings the most representative atributes.
Definition at line 396 of file growing_inputs.cpp.
| void write_XML | ( | tinyxml2::XMLPrinter & | file_stream | ) | const |
Serializes the growing inputs object into a XML document of the TinyXML library without keep the DOM tree in memory. See the OpenNN manual for more information about the format of this document.
Definition at line 490 of file growing_inputs.cpp.
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Maximum number of inputs in the neural network.
Definition at line 88 of file growing_inputs.h.
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Maximum number of epochs at which the selection error increases.
Definition at line 96 of file growing_inputs.h.
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Minimum number of inputs in the neural network.
Definition at line 92 of file growing_inputs.h.
1.9.2