net.sourceforge.cilib.neuralnetwork.foundation.measurements
Class DcPatternCount

java.lang.Object
  net.sourceforge.cilib.neuralnetwork.foundation.measurements.DcPatternCount

All Implemented Interfaces:

Serializable, Measurement, Cloneable

public class DcPatternCount
extends Object
implements Measurement

TODO: Complete this javadoc.

See Also:

Serialized Form

Constructor Summary

DcPatternCount()

DcPatternCount(DcPatternCount rhs)

Method Summary

DcPatternCount	getClone() Create a cloned copy of the current object and return it.
String	getDomain() Get the domain string representing what this measurement's results will conform to.
Type	getValue(Algorithm algorithm) Get the value of the measurement.

Methods inherited from class java.lang.Object

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

Constructor Detail

DcPatternCount

public DcPatternCount()

DcPatternCount

public DcPatternCount(DcPatternCount rhs)

Method Detail

getClone

public DcPatternCount getClone()

Description copied from interface: Measurement

Create a cloned copy of the current object and return it. In general the created copy will be a deep copy of the provided instance. As a result this operation an be quite expensive if used incorrectly.

Specified by:

getClone in interface Measurement

Specified by:

getClone in interface Cloneable

Returns:

An exact clone of the current object instance.

See Also:

Object.clone()

getDomain

public String getDomain()

Description copied from interface: Measurement

Get the domain string representing what this measurement's results will conform to.

Specified by:

getDomain in interface Measurement

Returns:

The Domain String representing the represenation of the measurement

getValue

public Type getValue(Algorithm algorithm)

Description copied from interface: Measurement

Get the value of the measurement. The represenation of the measurement will be based on the domain string defined Measurement.getDomain()

Specified by:

getValue in interface Measurement

Parameters:

algorithm - The algorithm to obtain the measurement from.

Returns:

The Type representing the value of the measurement.