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| | LowWeightsPruning (double pruning_rate) |
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| | LowWeightsPruning (double pruning_rate, std::shared_ptr< learning::linear::LineSearch > lineSearch) |
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| | LowWeightsPruning (const pugi::xml_document &model) |
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| Cleaver::PruningMethod | pruning_method () const |
| | Returns the pruning method of the algorithm. More...
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| bool | line_search_pre_pruning () const |
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| void | pruning (std::set< unsigned int > &pruned_estimators, std::shared_ptr< data::Dataset > dataset, std::shared_ptr< metric::ir::Metric > scorer) |
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| | Cleaver (double pruning_rate) |
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| | Cleaver (double pruning_rate, std::shared_ptr< learning::linear::LineSearch > lineSearch) |
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| | Cleaver (const pugi::xml_document &model) |
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| std::string | name () const |
| | Returns the name of the optimizer. More...
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| virtual bool | need_partial_score_dataset () const |
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| void | optimize (std::shared_ptr< quickrank::learning::LTR_Algorithm > algo, std::shared_ptr< quickrank::data::Dataset > training_dataset, std::shared_ptr< quickrank::data::Dataset > validation_dataset, std::shared_ptr< quickrank::metric::ir::Metric > metric, size_t partial_save, const std::string model_filename) |
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| virtual std::shared_ptr< data::Dataset > | filter_dataset (std::shared_ptr< data::Dataset > dataset, std::set< unsigned int > &pruned_estimators) const |
| | Process the dataset filtering out features with 0-weight. More...
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| virtual pugi::xml_document * | get_xml_model () const |
| | Return the xml model representing the current object. More...
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| virtual std::vector< float > & | get_weigths () |
| | Returns the learned weights. More...
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| bool | is_pre_learning () const |
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| | Optimization () |
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| | Optimization (const pugi::xml_document &model) |
| | Generates a LTR_Algorithm instance from a previously saved XML model. More...
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| virtual | ~Optimization ()=default |
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| | Optimization (const Optimization &other)=delete |
| | Avoid inefficient copy constructor. More...
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| Optimization & | operator= (const Optimization &)=delete |
| | Avoid inefficient copy assignment. More...
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| virtual void | optimize (std::shared_ptr< learning::LTR_Algorithm > algo, std::shared_ptr< data::Dataset > training_dataset, std::shared_ptr< data::Dataset > validation_dataset, std::shared_ptr< metric::ir::Metric > metric, size_t partial_save, const std::string model_filename)=0 |
| | Executes the optimization process. More...
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| virtual void | save (std::string model_filename, int suffix=-1) const |
| | Save the current model to the output_file. More...
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This implements random pruning strategy for pruning ensembles.