jsat.datatransform

Class Imputer

java.lang.Object

jsat.datatransform.Imputer

All Implemented Interfaces:

Serializable, Cloneable, DataTransform, InPlaceTransform

public class Imputer
extends Object
implements InPlaceTransform

Imputes missing values in a dataset by finding reasonable default values. For categorical features, the mode will always be used for imputing. Numeric values can change how the imputing value is selected by using the Imputer.NumericImputionMode enum.

Author:

Edward Raff

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Imputer.NumericImputionMode

Field Summary

Fields

Modifier and Type	Field and Description
protected int[]	cat_imputs The values to impute for missing numeric columns
protected double[]	numeric_imputs The values to impute for missing numeric columns

Constructor Summary

Constructors

Constructor and Description
Imputer(DataSet<?> data)
Imputer(DataSet<?> data, Imputer.NumericImputionMode mode)
Imputer(Imputer toCopy) Copy constructor

Method Summary

Modifier and Type	Method and Description
Imputer	clone()
void	fit(DataSet d) Fits this transform to the given dataset.
void	mutableTransform(DataPoint dp) Mutates the given data point.
boolean	mutatesNominal() By default returns false.
DataPoint	transform(DataPoint dp) Returns a new data point that is a transformation of the original data point.

Methods inherited from class java.lang.Object

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

Field Detail

cat_imputs

protected int[] cat_imputs

The values to impute for missing numeric columns

numeric_imputs

protected double[] numeric_imputs

The values to impute for missing numeric columns

Constructor Detail

Imputer

public Imputer(DataSet<?> data)

Imputer

public Imputer(DataSet<?> data,
               Imputer.NumericImputionMode mode)

Imputer

public Imputer(Imputer toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

Method Detail

fit

public void fit(DataSet d)

Description copied from interface: DataTransform

Fits this transform to the given dataset. Some transforms can only be learned from classification or regression datasets. If an incompatible dataset type is given, a FailedToFitException exception may be thrown.

Specified by:

fit in interface DataTransform

Parameters:

d - the dataset to fir this transform to

mutableTransform

public void mutableTransform(DataPoint dp)

Description copied from interface: InPlaceTransform

Mutates the given data point. This causes side effects, altering the data point to have the same value as the output of DataTransform.transform(jsat.classifiers.DataPoint).

Specified by:

mutableTransform in interface InPlaceTransform

Parameters:

dp - the data point to alter

mutatesNominal

public boolean mutatesNominal()

Description copied from interface: InPlaceTransform

By default returns false. Only returns true if this transform will mutableTransform the nominal feature values of a data point.

Specified by:

mutatesNominal in interface InPlaceTransform

Returns:

true if nominal feature values are mutated, false otherwise.

transform

public DataPoint transform(DataPoint dp)

Description copied from interface: DataTransform

Returns a new data point that is a transformation of the original data point. This new data point is a different object, but may contain the same references as the original data point. It is not guaranteed that you can mutate the transformed point without having a side effect on the original point.

Specified by:

transform in interface DataTransform

Parameters:

dp - the data point to apply a transformation to

Returns:

a transformed data point

clone

public Imputer clone()

Specified by:

clone in interface DataTransform

Overrides:

clone in class Object