#include <MLModelMetadata.h>

Collaboration diagram for MLModelMetadata:

Public Member Functions
	MLModelMetadata (const std::string &model_name, const MLModelType model_type, const std::string &model_type_str, const int64_t num_logical_features, const int64_t num_features, const int64_t num_categorical_features, const int64_t num_numeric_features, const std::string &model_metadata_json)

void	extractModelMetadata (const std::string &model_metadata_json, const int64_t num_logical_features)

const std::string &	getModelName () const

const MLModelType	getModelType () const

const std::string &	getModelTypeStr () const

int64_t	getNumLogicalFeatures () const

int64_t	getNumFeatures () const

int64_t	getNumCategoricalFeatures () const

int64_t	getNumNumericFeatures () const

const std::string &	getPredicted () const

const std::vector< std::string > &	getFeatures () const

const std::string &	getTrainingQuery () const

double	getDataSplitTrainFraction () const

double	getDataSplitEvalFraction () const

const std::vector< int64_t > &	getFeaturePermutations () const

Private Attributes
const std::string	model_name_

const MLModelType	model_type_

const std::string	model_type_str_

const int64_t	num_logical_features_

const int64_t	num_features_

const int64_t	num_categorical_features_

const int64_t	num_numeric_features_

std::string	predicted_

std::vector< std::string >	features_

std::string	training_query_

double	data_split_train_fraction_ {1.0}

double	data_split_eval_fraction_ {0.0}

std::vector< int64_t >	feature_permutations_

Detailed Description

Definition at line 24 of file MLModelMetadata.h.

Constructor & Destructor Documentation

MLModelMetadata::MLModelMetadata	(	const std::string &	model_name,
		const MLModelType	model_type,
		const std::string &	model_type_str,
		const int64_t	num_logical_features,
		const int64_t	num_features,
		const int64_t	num_categorical_features,
		const int64_t	num_numeric_features,
		const std::string &	model_metadata_json
	)

inline

Definition at line 26 of file MLModelMetadata.h.

References extractModelMetadata().

       : model_name_(model_name)
       , model_type_(model_type)
       , model_type_str_(model_type_str)
       , num_logical_features_(num_logical_features)
       , num_features_(num_features)
       , num_categorical_features_(num_categorical_features)
       , num_numeric_features_(num_numeric_features) {
     extractModelMetadata(model_metadata_json, num_logical_features);
   }

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Member Function Documentation

void MLModelMetadata::extractModelMetadata	(	const std::string &	model_metadata_json,
		const int64_t	num_logical_features
	)

Definition at line 23 of file MLModelMetadata.cpp.

References data_split_eval_fraction_, data_split_train_fraction_, feature_permutations_, features_, predicted_, and training_query_.

Referenced by MLModelMetadata().

                                                                                {
   rapidjson::Document model_metadata_doc;
   model_metadata_doc.Parse(model_metadata_json.c_str());
   if (model_metadata_doc.HasMember("predicted") &&
       model_metadata_doc["predicted"].IsString()) {
     predicted_ = model_metadata_doc["predicted"].GetString();
   }
   if (model_metadata_doc.HasMember("training_query") &&
       model_metadata_doc["training_query"].IsString()) {
     training_query_ = model_metadata_doc["training_query"].GetString();
   }
   if (model_metadata_doc.HasMember("features") &&
       model_metadata_doc["features"].IsArray()) {
     const rapidjson::Value& features_array = model_metadata_doc["features"];
     for (const auto& feature : features_array.GetArray()) {
       features_.emplace_back(feature.GetString());
     }
   } else {
     features_.resize(num_logical_features, "");
   }
   if (model_metadata_doc.HasMember("data_split_train_fraction") &&
       model_metadata_doc["data_split_train_fraction"].IsDouble()) {
     // Extract the double value
     data_split_train_fraction_ =
         model_metadata_doc["data_split_train_fraction"].GetDouble();
   }
   if (model_metadata_doc.HasMember("data_split_eval_fraction") &&
       model_metadata_doc["data_split_eval_fraction"].IsDouble()) {
     // Extract the double value
     data_split_eval_fraction_ =
         model_metadata_doc["data_split_eval_fraction"].GetDouble();
   }
   if (model_metadata_doc.HasMember("feature_permutations") &&
       model_metadata_doc["feature_permutations"].IsArray()) {
     const rapidjson::Value& feature_permutations_array =
         model_metadata_doc["feature_permutations"];
     for (const auto& feature_permutation : feature_permutations_array.GetArray()) {
       feature_permutations_.emplace_back(feature_permutation.GetInt64());
     }
   }
 }

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double MLModelMetadata::getDataSplitEvalFraction ( ) const

inline

Definition at line 58 of file MLModelMetadata.h.

References data_split_eval_fraction_.

58 { return data_split_eval_fraction_; }

MLModelMetadata::data_split_eval_fraction_

double data_split_eval_fraction_

Definition: MLModelMetadata.h:75

double MLModelMetadata::getDataSplitTrainFraction ( ) const

inline

Definition at line 57 of file MLModelMetadata.h.

References data_split_train_fraction_.

57 { return data_split_train_fraction_; }

MLModelMetadata::data_split_train_fraction_

double data_split_train_fraction_

Definition: MLModelMetadata.h:74

const std::vector<int64_t>& MLModelMetadata::getFeaturePermutations ( ) const

inline

Definition at line 59 of file MLModelMetadata.h.

References feature_permutations_.

                                                            {
     return feature_permutations_;
   }

const std::vector<std::string>& MLModelMetadata::getFeatures ( ) const

inline

Definition at line 55 of file MLModelMetadata.h.

References features_.

Referenced by ShowModelFeatureDetailsCommand::prepareLogicalValues().

55 { return features_; }

MLModelMetadata::features_

std::vector< std::string > features_

Definition: MLModelMetadata.h:72

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const std::string& MLModelMetadata::getModelName ( ) const

inline

Definition at line 47 of file MLModelMetadata.h.

References model_name_.

47 { return model_name_; }

MLModelMetadata::model_name_

const std::string model_name_

Definition: MLModelMetadata.h:64

const MLModelType MLModelMetadata::getModelType ( ) const

inline

Definition at line 48 of file MLModelMetadata.h.

References model_type_.

Referenced by ShowModelFeatureDetailsCommand::prepareLogicalValues().

48 { return model_type_; }

MLModelMetadata::model_type_

const MLModelType model_type_

Definition: MLModelMetadata.h:65

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const std::string& MLModelMetadata::getModelTypeStr ( ) const

inline

Definition at line 49 of file MLModelMetadata.h.

References model_type_str_.

49 { return model_type_str_; }

MLModelMetadata::model_type_str_

const std::string model_type_str_

Definition: MLModelMetadata.h:66

int64_t MLModelMetadata::getNumCategoricalFeatures ( ) const

inline

Definition at line 52 of file MLModelMetadata.h.

References num_categorical_features_.

52 { return num_categorical_features_; }

MLModelMetadata::num_categorical_features_

const int64_t num_categorical_features_

Definition: MLModelMetadata.h:69

int64_t MLModelMetadata::getNumFeatures ( ) const

inline

Definition at line 51 of file MLModelMetadata.h.

References num_features_.

51 { return num_features_; }

MLModelMetadata::num_features_

const int64_t num_features_

Definition: MLModelMetadata.h:68

int64_t MLModelMetadata::getNumLogicalFeatures ( ) const

inline

Definition at line 50 of file MLModelMetadata.h.

References num_logical_features_.

50 { return num_logical_features_; }

MLModelMetadata::num_logical_features_

const int64_t num_logical_features_

Definition: MLModelMetadata.h:67

int64_t MLModelMetadata::getNumNumericFeatures ( ) const

inline

Definition at line 53 of file MLModelMetadata.h.

References num_numeric_features_.

53 { return num_numeric_features_; }

MLModelMetadata::num_numeric_features_

const int64_t num_numeric_features_

Definition: MLModelMetadata.h:70

const std::string& MLModelMetadata::getPredicted ( ) const

inline

Definition at line 54 of file MLModelMetadata.h.

References predicted_.

54 { return predicted_; }

MLModelMetadata::predicted_

std::string predicted_

Definition: MLModelMetadata.h:71

const std::string& MLModelMetadata::getTrainingQuery ( ) const

inline

Definition at line 56 of file MLModelMetadata.h.

References training_query_.

56 { return training_query_; }

MLModelMetadata::training_query_

std::string training_query_

Definition: MLModelMetadata.h:73

Member Data Documentation

double MLModelMetadata::data_split_eval_fraction_ {0.0}

private

Definition at line 75 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getDataSplitEvalFraction().

double MLModelMetadata::data_split_train_fraction_ {1.0}

private

Definition at line 74 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getDataSplitTrainFraction().

std::vector<int64_t> MLModelMetadata::feature_permutations_

private

Definition at line 76 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getFeaturePermutations().

std::vector<std::string> MLModelMetadata::features_

private

Definition at line 72 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getFeatures().

const std::string MLModelMetadata::model_name_

private

Definition at line 64 of file MLModelMetadata.h.

Referenced by getModelName().

const MLModelType MLModelMetadata::model_type_

private

Definition at line 65 of file MLModelMetadata.h.

Referenced by getModelType().

const std::string MLModelMetadata::model_type_str_

private

Definition at line 66 of file MLModelMetadata.h.

Referenced by getModelTypeStr().

const int64_t MLModelMetadata::num_categorical_features_

private

Definition at line 69 of file MLModelMetadata.h.

Referenced by getNumCategoricalFeatures().

const int64_t MLModelMetadata::num_features_

private

Definition at line 68 of file MLModelMetadata.h.

Referenced by getNumFeatures().

const int64_t MLModelMetadata::num_logical_features_

private

Definition at line 67 of file MLModelMetadata.h.

Referenced by getNumLogicalFeatures().

const int64_t MLModelMetadata::num_numeric_features_

private

Definition at line 70 of file MLModelMetadata.h.

Referenced by getNumNumericFeatures().

std::string MLModelMetadata::predicted_

private

Definition at line 71 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getPredicted().

std::string MLModelMetadata::training_query_

private

Definition at line 73 of file MLModelMetadata.h.

Referenced by extractModelMetadata(), and getTrainingQuery().

The documentation for this class was generated from the following files:

/home/jenkins-slave/workspace/core-os-doxygen/QueryEngine/TableFunctions/SystemFunctions/os/ML/MLModelMetadata.h
/home/jenkins-slave/workspace/core-os-doxygen/QueryEngine/TableFunctions/SystemFunctions/os/ML/MLModelMetadata.cpp

Public Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation