AutoDeskewTransform (Java Statistical Analysis Tool 0.0.8 API)

java.lang.Object
- jsat.datatransform.AutoDeskewTransform

All Implemented Interfaces:

Serializable, Cloneable, DataTransform, InPlaceTransform
```
public class AutoDeskewTransform
extends Object
implements InPlaceTransform
```
This transform applies a shifted Box-Cox transform for several fixed values of λ, and selects the one that provides the greatest reduction in the skewness of the distribution. This is done in an attempt to make the individual features appear more normal. The shifted values are done to preserve zeros and keep sparse inputs sparse. This is done with two passes through the data set, but requires only O(D #λ values) memory.

The default values of λ are -1, -1/2, 0, 1/2, 1. When using negative λ values all zeros are skipped and left as zeros. λ = 1 is an implicit value that is always included regardless of the input, as it is equivalent to leaving the data unchanged when preserving zero values. The stated default values include the log(x+1) and sqrt(x) transforms that are commonly used for deskewing as special cases.

Skewness can be calculated by including zero, but by default ignores them as "not-present" values.

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors
Modifier	Constructor and Description
	`AutoDeskewTransform()` Creates a new AutoDeskew transform
`protected`	`AutoDeskewTransform(AutoDeskewTransform toCopy)` Copy constructor
	`AutoDeskewTransform(boolean ignorZeros, List<Double> lambdas)` Creates a new AutoDeskew transform
	`AutoDeskewTransform(DataSet dataSet)` Creates a new deskewing object from the given data set
	`AutoDeskewTransform(DataSet dataSet, boolean ignorZeros, List<Double> lambdas)` Creates a new deskewing object from the given data set
	`AutoDeskewTransform(DataSet dataSet, List<Double> lambdas)` Creates a new deskewing object from the given data set
	`AutoDeskewTransform(double... lambdas)` Creates a new AutoDeskew transform
	`AutoDeskewTransform(List<Double> lambdas)` Creates a new AutoDeskew transform

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`AutoDeskewTransform`	`clone()`
`void`	`fit(DataSet dataSet)` 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

- Constructor Detail
  - AutoDeskewTransform
```
public AutoDeskewTransform()
```
    Creates a new AutoDeskew transform
  - AutoDeskewTransform
```
public AutoDeskewTransform(double... lambdas)
```
    Creates a new AutoDeskew transform
    
    Parameters:
    
    lambdas - the list of lambda values to evaluate
  - AutoDeskewTransform
```
public AutoDeskewTransform(List<Double> lambdas)
```
    Creates a new AutoDeskew transform
    
    Parameters:
    
    lambdas - the list of lambda values to evaluate
  - AutoDeskewTransform
```
public AutoDeskewTransform(boolean ignorZeros,
                           List<Double> lambdas)
```
    Creates a new AutoDeskew transform
    
    Parameters:
    
    ignorZeros - true to ignore zero values when calculating the skewness, false to include them.
    
    lambdas - the list of lambda values to evaluate
  - AutoDeskewTransform
```
public AutoDeskewTransform(DataSet dataSet)
```
    Creates a new deskewing object from the given data set
    
    Parameters:
    
    dataSet - the data set to deskew
  - AutoDeskewTransform
```
public AutoDeskewTransform(DataSet dataSet,
                           List<Double> lambdas)
```
    Creates a new deskewing object from the given data set
    
    Parameters:
    
    dataSet - the data set to deskew
    
    lambdas - the list of lambda values to evaluate
  - AutoDeskewTransform
```
public AutoDeskewTransform(DataSet dataSet,
                           boolean ignorZeros,
                           List<Double> lambdas)
```
    Creates a new deskewing object from the given data set
    
    Parameters:
    
    dataSet - the data set to deskew
    
    ignorZeros - true to ignore zero values when calculating the skewness, false to include them.
    
    lambdas - the list of lambda values to evaluate
  - AutoDeskewTransform
```
protected AutoDeskewTransform(AutoDeskewTransform toCopy)
```
    Copy constructor
    
    Parameters:
    
    toCopy - the object to copy
- Method Detail
  - fit
```
public void fit(DataSet dataSet)
```
    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:
    
    dataSet - the dataset to fir this transform to
  - 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
  - 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
  - clone
```
public AutoDeskewTransform clone()
```
    Specified by:
    
    clone in interface DataTransform
    
    Overrides:
    
    clone in class Object
  - 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.

Class AutoDeskewTransform

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

AutoDeskewTransform

Method Detail

fit

transform

mutableTransform

clone

mutatesNominal