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## fr.lip6.kernel.extra.bag
Class SubListKernel<S,T extends java.util.ArrayList<S>>

    java.lang.Object
      fr.lip6.kernel.Kernel<T>
          fr.lip6.kernel.extra.bag.SubListKernel<S,T>

Type Parameters:
  `S` -
  `T` - type of element in the bag

All Implemented Interfaces:
  java.io.Serializable

    public class SubListKernel<S,T extends java.util.ArrayList<S>>

extends Kernel<T>
implements java.io.Serializable

Default kernel on bags : sum all kernel values involving an element from B1 and an element from B2 between specified bounds.

Author:
  dpicard
See Also:
  Serialized Form

Field Summary

Fields inherited from class fr.lip6.kernel.Kernel
`name`

Constructor Summary
`SubListKernel(int from, int to, Kernel<S> kernel)`

Method Summary
`double` | `valueOf(T t1)` kernel similarity to zero
`double` | `valueOf(T t1, T t2)` compute the kernel similarity between two element of input space

Methods inherited from class fr.lip6.kernel.Kernel
`getKernelMatrix, getNormalizedKernelMatrix, normalizedValueOf, setName, toString`

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

Constructor Detail

### SubListKernel

    public SubListKernel(int from,
                         int to,
                         Kernel<S> kernel)

Parameters:
  `from` - starting index of the bags
  `to` - end index of the bags
  `kernel` - minor kernel

Method Detail

### valueOf

    public double valueOf(T t1,
                          T t2)

  Description copied from class: `Kernel`
  compute the kernel similarity between two element of input space

  Specified by:
    `valueOf` in class `Kernel<T extends java.util.ArrayList<S>>`
  Parameters:
    `t1` - first element
    `t2` - second element
  Returns:
    the kernel value

### valueOf

    public double valueOf(T t1)

  Description copied from class: `Kernel`
  kernel similarity to zero

  Specified by:
    `valueOf` in class `Kernel<T extends java.util.ArrayList<S>>`
  Parameters:
    `t1` - the element to compute the similarity to zero

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