smile.base.svm

Class KernelMachine<T>

java.lang.Object

smile.base.svm.KernelMachine<T>

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

KernelMachine, SVM

public class KernelMachine<T>
extends java.lang.Object
implements java.io.Serializable

Kernel machines. Kernel methods owe their name to the use of kernel functions, which enable them to operate in a high-dimensional, implicit feature space without ever computing the coordinates of the data in that space, but rather by simply computing the inner products between the images of all pairs of data in the feature space.

Kernel methods can be thought of as instance-based learners: rather than learning some fixed set of parameters corresponding to the features of their inputs, they instead store (a subset of) their training set (or a new representation) and learn for it a corresponding weight. Prediction for unlabeled inputs is treated by the application of a similiarity function.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
KernelMachine(smile.math.kernel.MercerKernel<T> kernel, T[] instances, double[] weight) Constructor.
KernelMachine(smile.math.kernel.MercerKernel<T> kernel, T[] instances, double[] weight, double b) Constructor.

Method Summary

Modifier and Type	Method and Description
double	f(T x) Returns the decision function value.
T[]	instances() Returns the instances of kernel machines.
double	intercept() Returns the intercept.
smile.math.kernel.MercerKernel<T>	kernel() Returns the kernel function.
java.lang.String	toString()
SVM<T>	toSVM() Convert the kernel machine to SVM instance.
double[]	weights() Returns the weights of instances.

Methods inherited from class java.lang.Object

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

Constructor Detail

KernelMachine

public KernelMachine(smile.math.kernel.MercerKernel<T> kernel,
                     T[] instances,
                     double[] weight)

Constructor.

Parameters:

kernel - Kernel function.

instances - The instances in the kernel machine, e.g. support vectors.

weight - The weights of instances.

KernelMachine

public KernelMachine(smile.math.kernel.MercerKernel<T> kernel,
                     T[] instances,
                     double[] weight,
                     double b)

Constructor.

Parameters:

kernel - Kernel function.

instances - The instances in the kernel machine, e.g. support vectors.

weight - The weights of instances.

b - The intercept;

Method Detail

kernel

public smile.math.kernel.MercerKernel<T> kernel()

Returns the kernel function.

instances

public T[] instances()

Returns the instances of kernel machines.

weights

public double[] weights()

Returns the weights of instances.

intercept

public double intercept()

Returns the intercept.

f

public double f(T x)

Returns the decision function value.

toSVM

public SVM<T> toSVM()

Convert the kernel machine to SVM instance.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object