Synapseml: Synapse.ML.Featurize.Featurize Class Reference
Featurize implements Featurize More...
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[legend]Featurize implements Featurize
◆ Featurize() [1/2]
| Synapse.ML.Featurize.Featurize.Featurize | ( | | ) | |
| inline |
◆ Featurize() [2/2]
| Synapse.ML.Featurize.Featurize.Featurize | ( | string | uid | ) | |
| inline |
Creates a Featurize with a UID that is used to give the Featurize a unique ID.
Parameters| uid | An immutable unique ID for the object and its derivatives. |
| override PipelineModel Synapse.ML.Featurize.Featurize.Fit | ( | DataFrame | dataset | ) | |
Fits a model to the input data.
Parameters| dataset | The DataFrame to fit the model to. |
ReturnsPipelineModel◆ GetImputeMissing()
| bool Synapse.ML.Featurize.Featurize.GetImputeMissing | ( | | ) | |
Gets imputeMissing value
ReturnsimputeMissing: Whether to impute missing values◆ GetInputCols()
| string [] Synapse.ML.Featurize.Featurize.GetInputCols | ( | | ) | |
Gets inputCols value
ReturnsinputCols: The names of the input columns◆ GetNumFeatures()
| int Synapse.ML.Featurize.Featurize.GetNumFeatures | ( | | ) | |
Gets numFeatures value
ReturnsnumFeatures: Number of features to hash string columns to◆ GetOneHotEncodeCategoricals()
| bool Synapse.ML.Featurize.Featurize.GetOneHotEncodeCategoricals | ( | | ) | |
Gets oneHotEncodeCategoricals value
ReturnsoneHotEncodeCategoricals: One-hot encode categorical columns◆ GetOutputCol()
| string Synapse.ML.Featurize.Featurize.GetOutputCol | ( | | ) | |
Gets outputCol value
ReturnsoutputCol: The name of the output column| static Featurize Synapse.ML.Featurize.Featurize.Load | ( | string | path | ) | |
| static |
| JavaMLReader<Featurize> Synapse.ML.Featurize.Featurize.Read | ( | | ) | |
Get the corresponding JavaMLReader instance.
Returnsan JavaMLReader<Featurize> instance for this ML instance.| void Synapse.ML.Featurize.Featurize.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 |
◆ SetImputeMissing()
| Featurize Synapse.ML.Featurize.Featurize.SetImputeMissing | ( | bool | value | ) | |
Sets value for imputeMissing
Parameters| value | Whether to impute missing values |
ReturnsNew Featurize object◆ SetInputCols()
| Featurize Synapse.ML.Featurize.Featurize.SetInputCols | ( | string [] | value | ) | |
Sets value for inputCols
Parameters| value | The names of the input columns |
ReturnsNew Featurize object◆ SetNumFeatures()
| Featurize Synapse.ML.Featurize.Featurize.SetNumFeatures | ( | int | value | ) | |
Sets value for numFeatures
Parameters| value | Number of features to hash string columns to |
ReturnsNew Featurize object◆ SetOneHotEncodeCategoricals()
| Featurize Synapse.ML.Featurize.Featurize.SetOneHotEncodeCategoricals | ( | bool | value | ) | |
Sets value for oneHotEncodeCategoricals
Parameters| value | One-hot encode categorical columns |
ReturnsNew Featurize object◆ SetOutputCol()
| Featurize Synapse.ML.Featurize.Featurize.SetOutputCol | ( | string | value | ) | |
Sets value for outputCol
Parameters| value | The name of the output column |
ReturnsNew Featurize object The documentation for this class was generated from the following file:- synapse/ml/featurize/Featurize.cs
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Zora Stowers
Update: 2024-06-13