Synapse.ML.Automl.TuneHyperparameters Class Reference

TuneHyperparameters implements TuneHyperparameters More...

Inheritance diagram for Synapse.ML.Automl.TuneHyperparameters:

Collaboration diagram for Synapse.ML.Automl.TuneHyperparameters:

Public Member Functions
	TuneHyperparameters ()
	Creates a TuneHyperparameters without any parameters. More...
	TuneHyperparameters (string uid)
	Creates a TuneHyperparameters with a UID that is used to give the TuneHyperparameters a unique ID. More...
TuneHyperparameters	SetEvaluationMetric (string value)
	Sets value for evaluationMetric More...
TuneHyperparameters	SetModels (IEstimator< object >[] value)
	Sets value for models More...
TuneHyperparameters	SetNumFolds (int value)
	Sets value for numFolds More...
TuneHyperparameters	SetNumRuns (int value)
	Sets value for numRuns More...
TuneHyperparameters	SetParallelism (int value)
	Sets value for parallelism More...
TuneHyperparameters	SetParamSpace (object value)
	Sets value for paramSpace More...
TuneHyperparameters	SetSeed (long value)
	Sets value for seed More...
string	GetEvaluationMetric ()
	Gets evaluationMetric value More...
IEstimator< object > []	GetModels ()
	Gets models value More...
int	GetNumFolds ()
	Gets numFolds value More...
int	GetNumRuns ()
	Gets numRuns value More...
int	GetParallelism ()
	Gets parallelism value More...
object	GetParamSpace ()
	Gets paramSpace value More...
long	GetSeed ()
	Gets seed value More...
override TuneHyperparametersModel	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< TuneHyperparameters >	Read ()
	Get the corresponding JavaMLReader instance. More...

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

Detailed Description

TuneHyperparameters implements TuneHyperparameters

Constructor & Destructor Documentation

TuneHyperparameters() [1/2]

Synapse.ML.Automl.TuneHyperparameters.TuneHyperparameters ( )

inline

Creates a TuneHyperparameters without any parameters.

TuneHyperparameters() [2/2]

Synapse.ML.Automl.TuneHyperparameters.TuneHyperparameters ( string  uid )

inline

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

Parameters

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

Member Function Documentation

Fit()

override TuneHyperparametersModel Synapse.ML.Automl.TuneHyperparameters.Fit

(

DataFrame

dataset

)

Fits a model to the input data.

Parameters

dataset

The DataFrame to fit the model to.

Returns

TuneHyperparametersModel

GetEvaluationMetric()

string Synapse.ML.Automl.TuneHyperparameters.GetEvaluationMetric

(

)

Gets evaluationMetric value

Returns

evaluationMetric: Metric to evaluate models with

GetModels()

IEstimator<object> [] Synapse.ML.Automl.TuneHyperparameters.GetModels ( )

inline

Gets models value

Returns

models: Estimators to run

GetNumFolds()

int Synapse.ML.Automl.TuneHyperparameters.GetNumFolds

(

)

Gets numFolds value

Returns

numFolds: Number of folds

GetNumRuns()

int Synapse.ML.Automl.TuneHyperparameters.GetNumRuns

(

)

Gets numRuns value

Returns

numRuns: Termination criteria for randomized search

GetParallelism()

int Synapse.ML.Automl.TuneHyperparameters.GetParallelism

(

)

Gets parallelism value

Returns

parallelism: The number of models to run in parallel

GetParamSpace()

object Synapse.ML.Automl.TuneHyperparameters.GetParamSpace

(

)

Gets paramSpace value

Returns

paramSpace: Parameter space for generating hyperparameters

GetSeed()

long Synapse.ML.Automl.TuneHyperparameters.GetSeed

(

)

Gets seed value

Returns

seed: Random number generator seed

Load()

static TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.Load ( string  path )

static

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

Parameters

path	The path the previous TuneHyperparameters was saved to

Returns

New TuneHyperparameters object, loaded from path.

Read()

JavaMLReader<TuneHyperparameters> Synapse.ML.Automl.TuneHyperparameters.Read

(

)

Get the corresponding JavaMLReader instance.

Returns

an JavaMLReader<TuneHyperparameters> instance for this ML instance.

Save()

void Synapse.ML.Automl.TuneHyperparameters.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

SetEvaluationMetric()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetEvaluationMetric

(

string

value

)

Sets value for evaluationMetric

Parameters

value

Metric to evaluate models with

Returns

New TuneHyperparameters object

SetModels()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetModels

(

IEstimator< object > []

value

)

Sets value for models

Parameters

value

Estimators to run

Returns

New TuneHyperparameters object

SetNumFolds()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetNumFolds

(

int

value

)

Sets value for numFolds

Parameters

value

Number of folds

Returns

New TuneHyperparameters object

SetNumRuns()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetNumRuns

(

int

value

)

Sets value for numRuns

Parameters

value

Termination criteria for randomized search

Returns

New TuneHyperparameters object

SetParallelism()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetParallelism

(

int

value

)

Sets value for parallelism

Parameters

value

The number of models to run in parallel

Returns

New TuneHyperparameters object

SetParamSpace()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetParamSpace

(

object

value

)

Sets value for paramSpace

Parameters

value

Parameter space for generating hyperparameters

Returns

New TuneHyperparameters object

SetSeed()

TuneHyperparameters Synapse.ML.Automl.TuneHyperparameters.SetSeed

(

long

value

)

Sets value for seed

Parameters

value

Random number generator seed

Returns

New TuneHyperparameters object

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

• synapse/ml/automl/TuneHyperparameters.cs