Package smile.feature.extraction

Class SparseEncoder

java.lang.Object

smile.feature.extraction.SparseEncoder

All Implemented Interfaces:

Function<smile.data.Tuple,smile.util.SparseArray>

public class SparseEncoder
extends Object
implements Function<smile.data.Tuple,smile.util.SparseArray>

Encodes numeric and categorical features into sparse array with on-hot encoding of categorical variables.

Constructor Summary

Constructors

Constructor	Description
SparseEncoder(smile.data.type.StructType schema, String... columns)	Constructor.

Method Summary

Modifier and Type	Method	Description
smile.util.SparseArray[]	apply(smile.data.DataFrame data)	Generates the sparse representation of a data frame.
smile.util.SparseArray	apply(smile.data.Tuple x)	Generates the sparse representation of given object.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface java.util.function.Function

andThen, compose

Constructor Details

SparseEncoder

public SparseEncoder(smile.data.type.StructType schema,
 String... columns)

Constructor.

Parameters:

schema - the data frame schema.

columns - the column names of variables to encode. If empty, all numeric and categorical columns will be used.

Method Details

apply

public smile.util.SparseArray apply(smile.data.Tuple x)

Generates the sparse representation of given object.

Specified by:

apply in interface Function<smile.data.Tuple,smile.util.SparseArray>

Parameters:

x - an object of interest.

Returns:

the sparse feature vector.

apply

public smile.util.SparseArray[] apply(smile.data.DataFrame data)

Generates the sparse representation of a data frame.

Parameters:

data - a data frame.

Returns:

the sparse feature vectors.