SparseVector.NormalizingKernel (BioJava-1.7.1 API)

java.lang.Object
- org.biojava.stats.svm.SparseVector.NormalizingKernel

All Implemented Interfaces:

java.io.Serializable, SVMKernel

Enclosing class:

SparseVector
```
public static class SparseVector.NormalizingKernel
extends java.lang.Object
implements SVMKernel, java.io.Serializable
```
A version of the standard dot-product kernel that scales each column independently.

Author:

Matthew Pocock

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor	Description
`NormalizingKernel(java.util.List vectors)`	Generate a normalizing kernel defined by the SparseVectors in vectors.
`NormalizingKernel(SparseVector s)`	Generate a normalizing kernel with the normalizing vector s.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`evaluate(java.lang.Object o1, java.lang.Object o2)`	Evaluate the kernel function between two SparseVectors.
`SparseVector`	`getNormalizingVector()`	Retrive the current normalizing vector.
`void`	`setNormalizingVector(SparseVector nv)`	Set the normalizing vector.
`java.lang.String`	`toString()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - NormalizingKernel
```
public NormalizingKernel(SparseVector s)
```
    Generate a normalizing kernel with the normalizing vector s.
    
    Parameters:
    
    s - the SparseVector to normalize by
  - NormalizingKernel
```
public NormalizingKernel(java.util.List vectors)
```
    Generate a normalizing kernel defined by the SparseVectors in vectors.
    It will set up a normalizing vector that has weight that will scale each element so that the average score is 1.
- Method Detail
  - getNormalizingVector
```
public SparseVector getNormalizingVector()
```
    Retrive the current normalizing vector.
    
    Returns:
    
    the normalizing vector
  - setNormalizingVector
```
public void setNormalizingVector(SparseVector nv)
```
    Set the normalizing vector.
    
    Parameters:
    
    nv - the new normalizing vector
  - evaluate
```
public double evaluate(java.lang.Object o1,
                       java.lang.Object o2)
```
    Evaluate the kernel function between two SparseVectors.
    This function is equivalent to:
    k(a, b) = sum_i ( a_i * b_i * nv_i )
    where nv_i is the value of the normalizing vector at index i. This can be thought of as scaling each vector at index i by sqrt(nv_i).
    
    Specified by:
    
    evaluate in interface SVMKernel
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object