Synapse.ML.Train.TrainRegressor Class Reference

TrainRegressor implements TrainRegressor More...

Inheritance diagram for Synapse.ML.Train.TrainRegressor:

Collaboration diagram for Synapse.ML.Train.TrainRegressor:

Public Member Functions
	TrainRegressor ()
	Creates a TrainRegressor without any parameters. More...
	TrainRegressor (string uid)
	Creates a TrainRegressor with a UID that is used to give the TrainRegressor a unique ID. More...
TrainRegressor	SetFeaturesCol (string value)
	Sets value for featuresCol More...
TrainRegressor	SetLabelCol (string value)
	Sets value for labelCol More...
TrainRegressor	SetModel< M > (JavaEstimator< M > value)
	Sets value for model More...
TrainRegressor	SetNumFeatures (int value)
	Sets value for numFeatures More...
string	GetFeaturesCol ()
	Gets featuresCol value More...
string	GetLabelCol ()
	Gets labelCol value More...
IEstimator< object >	GetModel ()
	Gets model value More...
int	GetNumFeatures ()
	Gets numFeatures value More...
override TrainedRegressorModel	Fit (DataFrame dataset)
	Fits a model to the input data. 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< TrainRegressor >	Read ()
	Get the corresponding JavaMLReader instance. More...

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

Detailed Description

TrainRegressor implements TrainRegressor

Constructor & Destructor Documentation

TrainRegressor() [1/2]

Synapse.ML.Train.TrainRegressor.TrainRegressor ( )

inline

Creates a TrainRegressor without any parameters.

TrainRegressor() [2/2]

Synapse.ML.Train.TrainRegressor.TrainRegressor ( string  uid )

inline

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

Parameters

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

Member Function Documentation

Fit()

override TrainedRegressorModel Synapse.ML.Train.TrainRegressor.Fit

(

DataFrame

dataset

)

Fits a model to the input data.

Parameters

dataset

The DataFrame to fit the model to.

Returns

TrainedRegressorModel

GetFeaturesCol()

string Synapse.ML.Train.TrainRegressor.GetFeaturesCol

(

)

Gets featuresCol value

Returns

featuresCol: The name of the features column

GetLabelCol()

string Synapse.ML.Train.TrainRegressor.GetLabelCol

(

)

Gets labelCol value

Returns

labelCol: The name of the label column

GetModel()

IEstimator<object> Synapse.ML.Train.TrainRegressor.GetModel ( )

inline

Gets model value

Returns

model: Regressor to run

GetNumFeatures()

int Synapse.ML.Train.TrainRegressor.GetNumFeatures

(

)

Gets numFeatures value

Returns

numFeatures: Number of features to hash to

Load()

static TrainRegressor Synapse.ML.Train.TrainRegressor.Load ( string  path )

static

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

Parameters

path	The path the previous TrainRegressor was saved to

Returns

New TrainRegressor object, loaded from path.

Read()

JavaMLReader<TrainRegressor> Synapse.ML.Train.TrainRegressor.Read

(

)

Get the corresponding JavaMLReader instance.

Returns

an JavaMLReader<TrainRegressor> instance for this ML instance.

Save()

void Synapse.ML.Train.TrainRegressor.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

SetFeaturesCol()

TrainRegressor Synapse.ML.Train.TrainRegressor.SetFeaturesCol

(

string

value

)

Sets value for featuresCol

Parameters

value

The name of the features column

Returns

New TrainRegressor object

SetLabelCol()

TrainRegressor Synapse.ML.Train.TrainRegressor.SetLabelCol

(

string

value

)

Sets value for labelCol

Parameters

value

The name of the label column

Returns

New TrainRegressor object

SetModel< M >()

TrainRegressor Synapse.ML.Train.TrainRegressor.SetModel< M >

(

JavaEstimator< M >

value

)

Sets value for model

Parameters

value

Regressor to run

Returns

New TrainRegressor object

Type Constraints

M	:	JavaModel<M>
M	:	WrapAsTrainRegressor
M	:	Reference.Invoke
M	:	setModel
M	:	object
M	:	value

SetNumFeatures()

TrainRegressor Synapse.ML.Train.TrainRegressor.SetNumFeatures

(

int

value

)

Sets value for numFeatures

Parameters

value

Number of features to hash to

Returns

New TrainRegressor object

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

• synapse/ml/train/TrainRegressor.cs