Synapseml  1.0.2
Public Member Functions | Static Public Member Functions | List of all members
Synapse.ML.Featurize.CleanMissingData Class Reference

CleanMissingData implements CleanMissingData More...

Inheritance diagram for Synapse.ML.Featurize.CleanMissingData:
Inheritance graph
[legend]
Collaboration diagram for Synapse.ML.Featurize.CleanMissingData:
Collaboration graph
[legend]

Public Member Functions

 CleanMissingData ()
 Creates a CleanMissingData without any parameters. More...
 
 CleanMissingData (string uid)
 Creates a CleanMissingData with a UID that is used to give the CleanMissingData a unique ID. More...
 
CleanMissingData SetCleaningMode (string value)
 Sets value for cleaningMode More...
 
CleanMissingData SetCustomValue (string value)
 Sets value for customValue More...
 
CleanMissingData SetInputCols (string[] value)
 Sets value for inputCols More...
 
CleanMissingData SetOutputCols (string[] value)
 Sets value for outputCols More...
 
string GetCleaningMode ()
 Gets cleaningMode value More...
 
string GetCustomValue ()
 Gets customValue value More...
 
string[] GetInputCols ()
 Gets inputCols value More...
 
string[] GetOutputCols ()
 Gets outputCols value More...
 
override CleanMissingDataModel 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< CleanMissingDataRead ()
 Get the corresponding JavaMLReader instance. More...
 

Static Public Member Functions

static CleanMissingData Load (string path)
 Loads the CleanMissingData that was previously saved using Save(string). More...
 

Detailed Description

CleanMissingData implements CleanMissingData

Constructor & Destructor Documentation

◆ CleanMissingData() [1/2]

Synapse.ML.Featurize.CleanMissingData.CleanMissingData ( )
inline

Creates a CleanMissingData without any parameters.

◆ CleanMissingData() [2/2]

Synapse.ML.Featurize.CleanMissingData.CleanMissingData ( string  uid)
inline

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

Parameters
uidAn immutable unique ID for the object and its derivatives.

Member Function Documentation

◆ Fit()

override CleanMissingDataModel Synapse.ML.Featurize.CleanMissingData.Fit ( DataFrame  dataset)

Fits a model to the input data.

Parameters
datasetThe DataFrame to fit the model to.
Returns
CleanMissingDataModel

◆ GetCleaningMode()

string Synapse.ML.Featurize.CleanMissingData.GetCleaningMode ( )

Gets cleaningMode value

Returns
cleaningMode: Cleaning mode

◆ GetCustomValue()

string Synapse.ML.Featurize.CleanMissingData.GetCustomValue ( )

Gets customValue value

Returns
customValue: Custom value for replacement

◆ GetInputCols()

string [] Synapse.ML.Featurize.CleanMissingData.GetInputCols ( )

Gets inputCols value

Returns
inputCols: The names of the input columns

◆ GetOutputCols()

string [] Synapse.ML.Featurize.CleanMissingData.GetOutputCols ( )

Gets outputCols value

Returns
outputCols: The names of the output columns

◆ Load()

static CleanMissingData Synapse.ML.Featurize.CleanMissingData.Load ( string  path)
static

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

Parameters
pathThe path the previous CleanMissingData was saved to
Returns
New CleanMissingData object, loaded from path.

◆ Read()

JavaMLReader<CleanMissingData> Synapse.ML.Featurize.CleanMissingData.Read ( )

Get the corresponding JavaMLReader instance.

Returns
an JavaMLReader<CleanMissingData> instance for this ML instance.

◆ Save()

void Synapse.ML.Featurize.CleanMissingData.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
pathThe path to save the object to

◆ SetCleaningMode()

CleanMissingData Synapse.ML.Featurize.CleanMissingData.SetCleaningMode ( string  value)

Sets value for cleaningMode

Parameters
valueCleaning mode
Returns
New CleanMissingData object

◆ SetCustomValue()

CleanMissingData Synapse.ML.Featurize.CleanMissingData.SetCustomValue ( string  value)

Sets value for customValue

Parameters
valueCustom value for replacement
Returns
New CleanMissingData object

◆ SetInputCols()

CleanMissingData Synapse.ML.Featurize.CleanMissingData.SetInputCols ( string[]  value)

Sets value for inputCols

Parameters
valueThe names of the input columns
Returns
New CleanMissingData object

◆ SetOutputCols()

CleanMissingData Synapse.ML.Featurize.CleanMissingData.SetOutputCols ( string[]  value)

Sets value for outputCols

Parameters
valueThe names of the output columns
Returns
New CleanMissingData object

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