weka.classifiers.functions

Class MultilayerPerceptron.NeuralEnd

java.lang.Object

weka.classifiers.functions.neural.NeuralConnection

weka.classifiers.functions.MultilayerPerceptron.NeuralEnd

All Implemented Interfaces:

java.io.Serializable, RevisionHandler

Enclosing class:

MultilayerPerceptron

protected class MultilayerPerceptron.NeuralEnd
extends NeuralConnection

This inner class is used to connect the nodes in the network up to the data that they are classifying, Note that objects of this class are only suitable to go on the attribute side or class side of the network and not both.

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.functions.neural.NeuralConnection

CONNECTED, INPUT, m_id, m_inputList, m_inputNums, m_numInputs, m_numOutputs, m_outputList, m_outputNums, m_type, m_unitError, m_unitValue, m_weightsUpdated, m_x, m_y, OUTPUT, PURE_INPUT, PURE_OUTPUT, UNCONNECTED

Constructor Summary

Constructors

Constructor and Description
NeuralEnd(java.lang.String id) Constructor

Method Summary

Modifier and Type	Method and Description
void	drawHighlight(java.awt.Graphics g, int w, int h) Call this function to draw the node highlighted.
void	drawNode(java.awt.Graphics g, int w, int h) This will draw the node id to the graphics context.
double	errorValue(boolean calculate) Call this to get the error value of this unit, which in this case is the difference between the predicted class, and the actual class.
int	getLink()
java.lang.String	getRevision() Returns the revision string.
boolean	onUnit(java.awt.Graphics g, int x, int y, int w, int h) Call this function to determine if the point at x,y is on the unit.
double	outputValue(boolean calculate) Call this to get the output value of this unit.
void	reset() Call this to reset the value and error for this unit, ready for the next run.
void	restoreWeights() Call this to have the connection restore from the saved weights.
void	saveWeights() Call this to have the connection save the current weights.
void	setLink(boolean input, int val) Call this function to set What this end unit represents.

Methods inherited from class weka.classifiers.functions.neural.NeuralConnection

allocateInputs, allocateOutputs, changeInputNum, changeOutputNum, connect, connectInput, connectOutput, disconnect, disconnectInput, disconnectOutput, drawInputLines, drawOutputLines, getId, getInputNums, getInputs, getNumInputs, getNumOutputs, getOutputNums, getOutputs, getType, getX, getY, removeAllInputs, removeAllOutputs, setType, setX, setY, updateWeights, weightValue

Methods inherited from class java.lang.Object

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

Constructor Detail

NeuralEnd

public NeuralEnd(java.lang.String id)

Constructor

Method Detail

onUnit

public boolean onUnit(java.awt.Graphics g,
                      int x,
                      int y,
                      int w,
                      int h)

Call this function to determine if the point at x,y is on the unit.

Overrides:

onUnit in class NeuralConnection

Parameters:

g - The graphics context for font size info.

x - The x coord.

y - The y coord.

w - The width of the display.

h - The height of the display.

Returns:

True if the point is on the unit, false otherwise.

drawNode

public void drawNode(java.awt.Graphics g,
                     int w,
                     int h)

This will draw the node id to the graphics context.

Overrides:

drawNode in class NeuralConnection

Parameters:

g - The graphics context.

w - The width of the drawing area.

h - The height of the drawing area.

drawHighlight

public void drawHighlight(java.awt.Graphics g,
                          int w,
                          int h)

Call this function to draw the node highlighted.

Overrides:

drawHighlight in class NeuralConnection

Parameters:

g - The graphics context.

w - The width of the drawing area.

h - The height of the drawing area.

outputValue

public double outputValue(boolean calculate)

Call this to get the output value of this unit.

Specified by:

outputValue in class NeuralConnection

Parameters:

calculate - True if the value should be calculated if it hasn't been already.

Returns:

The output value, or NaN, if the value has not been calculated.

errorValue

public double errorValue(boolean calculate)

Call this to get the error value of this unit, which in this case is the difference between the predicted class, and the actual class.

Specified by:

errorValue in class NeuralConnection

Parameters:

calculate - True if the value should be calculated if it hasn't been already.

Returns:

The error value, or NaN, if the value has not been calculated.

reset

public void reset()

Call this to reset the value and error for this unit, ready for the next run. This will also call the reset function of all units that are connected as inputs to this one. This is also the time that the update for the listeners will be performed.

Specified by:

reset in class NeuralConnection

saveWeights

public void saveWeights()

Call this to have the connection save the current weights.

Specified by:

saveWeights in class NeuralConnection

restoreWeights

public void restoreWeights()

Call this to have the connection restore from the saved weights.

Specified by:

restoreWeights in class NeuralConnection

setLink

public void setLink(boolean input,
                    int val)
             throws java.lang.Exception

Call this function to set What this end unit represents.

Parameters:

input - True if this unit is used for entering an attribute, False if it's used for determining a class value.

val - The attribute number or class type that this unit represents. (for nominal attributes).

Throws:

java.lang.Exception

getLink

public int getLink()

Returns:

link for this node.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Returns:

the revision