LightGBMClassificationModel implements LightGBMClassificationModel More...

Inheritance diagram for Synapse.ML.Lightgbm.LightGBMClassificationModel:

Collaboration diagram for Synapse.ML.Lightgbm.LightGBMClassificationModel:

Public Member Functions
	LightGBMClassificationModel ()
	Creates a LightGBMClassificationModel without any parameters. More...

	LightGBMClassificationModel (string uid)
	Creates a LightGBMClassificationModel with a UID that is used to give the LightGBMClassificationModel a unique ID. More...

LightGBMClassificationModel	SetActualNumClasses (int value)
	Sets value for actualNumClasses More...

LightGBMClassificationModel	SetFeaturesCol (string value)
	Sets value for featuresCol More...

LightGBMClassificationModel	SetFeaturesShapCol (string value)
	Sets value for featuresShapCol More...

LightGBMClassificationModel	SetLabelCol (string value)
	Sets value for labelCol More...

LightGBMClassificationModel	SetLeafPredictionCol (string value)
	Sets value for leafPredictionCol More...

LightGBMClassificationModel	SetLightGBMBooster (LightGBMBooster value)
	Sets value for lightGBMBooster More...

LightGBMClassificationModel	SetNumIterations (int value)
	Sets value for numIterations More...

LightGBMClassificationModel	SetPredictDisableShapeCheck (bool value)
	Sets value for predictDisableShapeCheck More...

LightGBMClassificationModel	SetPredictionCol (string value)
	Sets value for predictionCol More...

LightGBMClassificationModel	SetProbabilityCol (string value)
	Sets value for probabilityCol More...

LightGBMClassificationModel	SetRawPredictionCol (string value)
	Sets value for rawPredictionCol More...

LightGBMClassificationModel	SetStartIteration (int value)
	Sets value for startIteration More...

LightGBMClassificationModel	SetThresholds (double[] value)
	Sets value for thresholds More...

int	GetActualNumClasses ()
	Gets actualNumClasses value More...

string	GetFeaturesCol ()
	Gets featuresCol value More...

string	GetFeaturesShapCol ()
	Gets featuresShapCol value More...

string	GetLabelCol ()
	Gets labelCol value More...

string	GetLeafPredictionCol ()
	Gets leafPredictionCol value More...

LightGBMBooster	GetLightGBMBooster ()
	Gets lightGBMBooster value More...

int	GetNumIterations ()
	Gets numIterations value More...

bool	GetPredictDisableShapeCheck ()
	Gets predictDisableShapeCheck value More...

string	GetPredictionCol ()
	Gets predictionCol value More...

string	GetProbabilityCol ()
	Gets probabilityCol value More...

string	GetRawPredictionCol ()
	Gets rawPredictionCol value More...

int	GetStartIteration ()
	Gets startIteration value More...

double []	GetThresholds ()
	Gets thresholds value More...

void	Save (string path)
	Saves the object so that it can be loaded later using Load. Note that these objects can be shared with Scala by Loading or Saving in Scala. More...

JavaMLWriter	Write ()
	Returns a JavaMLWriter instance for this ML instance.

JavaMLReader< LightGBMClassificationModel >	Read ()
	Get the corresponding JavaMLReader instance. More...

Static Public Member Functions
static LightGBMClassificationModel	Load (string path)
	Loads the LightGBMClassificationModel that was previously saved using Save(string). More...

Detailed Description

LightGBMClassificationModel implements LightGBMClassificationModel

Constructor & Destructor Documentation

◆ LightGBMClassificationModel() [1/2]

Synapse.ML.Lightgbm.LightGBMClassificationModel.LightGBMClassificationModel ( )

inline

Creates a LightGBMClassificationModel without any parameters.

◆ LightGBMClassificationModel() [2/2]

Synapse.ML.Lightgbm.LightGBMClassificationModel.LightGBMClassificationModel ( string uid )

inline

Creates a LightGBMClassificationModel with a UID that is used to give the LightGBMClassificationModel a unique ID.

Parameters

uid	An immutable unique ID for the object and its derivatives.

Member Function Documentation

◆ GetActualNumClasses()

int Synapse.ML.Lightgbm.LightGBMClassificationModel.GetActualNumClasses ( )

Gets actualNumClasses value

Returns: actualNumClasses: Inferred number of classes based on dataset metadata or, if there is no metadata, unique count

◆ GetFeaturesCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetFeaturesCol ( )

Gets featuresCol value

Returns: featuresCol: features column name

◆ GetFeaturesShapCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetFeaturesShapCol ( )

Gets featuresShapCol value

Returns: featuresShapCol: Output SHAP vector column name after prediction containing the feature contribution values

◆ GetLabelCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetLabelCol ( )

Gets labelCol value

Returns: labelCol: label column name

◆ GetLeafPredictionCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetLeafPredictionCol ( )

Gets leafPredictionCol value

Returns: leafPredictionCol: Predicted leaf indices's column name

◆ GetLightGBMBooster()

LightGBMBooster Synapse.ML.Lightgbm.LightGBMClassificationModel.GetLightGBMBooster ( )

Gets lightGBMBooster value

Returns: lightGBMBooster: The trained LightGBM booster

◆ GetNumIterations()

int Synapse.ML.Lightgbm.LightGBMClassificationModel.GetNumIterations ( )

Gets numIterations value

Returns: numIterations: Sets the total number of iterations used in the prediction.If <= 0, all iterations from start_iteration are used (no limits).

◆ GetPredictDisableShapeCheck()

bool Synapse.ML.Lightgbm.LightGBMClassificationModel.GetPredictDisableShapeCheck ( )

Gets predictDisableShapeCheck value

Returns: predictDisableShapeCheck: control whether or not LightGBM raises an error when you try to predict on data with a different number of features than the training data

◆ GetPredictionCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetPredictionCol ( )

Gets predictionCol value

Returns: predictionCol: prediction column name

◆ GetProbabilityCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetProbabilityCol ( )

Gets probabilityCol value

Returns: probabilityCol: Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities

◆ GetRawPredictionCol()

string Synapse.ML.Lightgbm.LightGBMClassificationModel.GetRawPredictionCol ( )

Gets rawPredictionCol value

Returns: rawPredictionCol: raw prediction (a.k.a. confidence) column name

◆ GetStartIteration()

int Synapse.ML.Lightgbm.LightGBMClassificationModel.GetStartIteration ( )

Gets startIteration value

Returns: startIteration: Sets the start index of the iteration to predict. If <= 0, starts from the first iteration.

◆ GetThresholds()

double [] Synapse.ML.Lightgbm.LightGBMClassificationModel.GetThresholds ( )

Gets thresholds value

Returns: thresholds: Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold

◆ Load()

static LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.Load ( string path )

static

Loads the LightGBMClassificationModel that was previously saved using Save(string).

Parameters

path	The path the previous LightGBMClassificationModel was saved to

Returns: New LightGBMClassificationModel object, loaded from path.

◆ Read()

JavaMLReader<LightGBMClassificationModel> Synapse.ML.Lightgbm.LightGBMClassificationModel.Read ( )

Get the corresponding JavaMLReader instance.

Returns: an JavaMLReader<LightGBMClassificationModel> instance for this ML instance.

◆ Save()

void Synapse.ML.Lightgbm.LightGBMClassificationModel.Save ( string path )

Saves the object so that it can be loaded later using Load. Note that these objects can be shared with Scala by Loading or Saving in Scala.

Parameters

path	The path to save the object to

◆ SetActualNumClasses()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetActualNumClasses ( int value )

Sets value for actualNumClasses

Parameters

value Inferred number of classes based on dataset metadata or, if there is no metadata, unique count

Returns: New LightGBMClassificationModel object

◆ SetFeaturesCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetFeaturesCol ( string value )

Sets value for featuresCol

Parameters

value features column name

Returns: New LightGBMClassificationModel object

◆ SetFeaturesShapCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetFeaturesShapCol ( string value )

Sets value for featuresShapCol

Parameters

value Output SHAP vector column name after prediction containing the feature contribution values

Returns: New LightGBMClassificationModel object

◆ SetLabelCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetLabelCol ( string value )

Sets value for labelCol

Parameters

value label column name

Returns: New LightGBMClassificationModel object

◆ SetLeafPredictionCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetLeafPredictionCol ( string value )

Sets value for leafPredictionCol

Parameters

value Predicted leaf indices's column name

Returns: New LightGBMClassificationModel object

◆ SetLightGBMBooster()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetLightGBMBooster ( LightGBMBooster value )

Sets value for lightGBMBooster

Parameters

value The trained LightGBM booster

Returns: New LightGBMClassificationModel object

◆ SetNumIterations()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetNumIterations ( int value )

Sets value for numIterations

Parameters

value Sets the total number of iterations used in the prediction.If <= 0, all iterations from start_iteration are used (no limits).

Returns: New LightGBMClassificationModel object

◆ SetPredictDisableShapeCheck()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetPredictDisableShapeCheck ( bool value )

Sets value for predictDisableShapeCheck

Parameters

value control whether or not LightGBM raises an error when you try to predict on data with a different number of features than the training data

Returns: New LightGBMClassificationModel object

◆ SetPredictionCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetPredictionCol ( string value )

Sets value for predictionCol

Parameters

value prediction column name

Returns: New LightGBMClassificationModel object

◆ SetProbabilityCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetProbabilityCol ( string value )

Sets value for probabilityCol

Parameters

value Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities

Returns: New LightGBMClassificationModel object

◆ SetRawPredictionCol()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetRawPredictionCol ( string value )

Sets value for rawPredictionCol

Parameters

value raw prediction (a.k.a. confidence) column name

Returns: New LightGBMClassificationModel object

◆ SetStartIteration()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetStartIteration ( int value )

Sets value for startIteration

Parameters

value Sets the start index of the iteration to predict. If <= 0, starts from the first iteration.

Returns: New LightGBMClassificationModel object

◆ SetThresholds()

LightGBMClassificationModel Synapse.ML.Lightgbm.LightGBMClassificationModel.SetThresholds ( double [] value )

Sets value for thresholds

Parameters

value Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold

Returns: New LightGBMClassificationModel object

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

synapse/ml/lightgbm/LightGBMClassificationModel.cs

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ LightGBMClassificationModel() [1/2]

◆ LightGBMClassificationModel() [2/2]

Member Function Documentation

◆ GetActualNumClasses()

◆ GetFeaturesCol()

◆ GetFeaturesShapCol()

◆ GetLabelCol()

◆ GetLeafPredictionCol()

◆ GetLightGBMBooster()

◆ GetNumIterations()

◆ GetPredictDisableShapeCheck()

◆ GetPredictionCol()

◆ GetProbabilityCol()

◆ GetRawPredictionCol()

◆ GetStartIteration()

◆ GetThresholds()

◆ Load()

◆ Read()

◆ Save()

◆ SetActualNumClasses()

◆ SetFeaturesCol()

◆ SetFeaturesShapCol()

◆ SetLabelCol()

◆ SetLeafPredictionCol()

◆ SetLightGBMBooster()

◆ SetNumIterations()

◆ SetPredictDisableShapeCheck()

◆ SetPredictionCol()

◆ SetProbabilityCol()

◆ SetRawPredictionCol()

◆ SetStartIteration()

◆ SetThresholds()