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JMSLTM Numerical Library 4.0 | ||||||||
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java.lang.Object com.imsl.datamining.neural.Network
Neural network base class.
Constructor Summary | |
Network()
Default constructor for Network. |
Method Summary | |
double[] |
computeStatistics(double[][] xData,
double[][] yData)
Computes error statistics. |
abstract HiddenLayer |
createHiddenLayer()
Creates the next HiddenLayer in the Network . |
abstract double[] |
forecast(double[] x)
Returns a forecast for each of the Network 's outputs
computed from the trained Network . |
abstract double[][] |
getForecastGradient(double[] x)
Returns the derivatives of the outputs with respect to the weights. |
abstract InputLayer |
getInputLayer()
Returns the InputLayer object. |
abstract Link[] |
getLinks()
Returns an array containing the Link objects in the
Network . |
abstract int |
getNumberOfInputs()
Returns the number of Network inputs. |
abstract int |
getNumberOfLinks()
Returns the number of Network Link s among the
node s. |
abstract int |
getNumberOfOutputs()
Returns the number of Network output Perceptron s. |
abstract int |
getNumberOfWeights()
Returns the number of weights in the Network . |
abstract OutputLayer |
getOutputLayer()
Returns the OutputLayer . |
abstract Perceptron[] |
getPerceptrons()
Returns an array containing the Perceptron s in the
Network . |
abstract double[] |
getWeights()
Returns the weights. |
abstract void |
setWeights(double[] weights)
Sets the weights. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public Network()
Network
.
Method Detail |
public double[] computeStatistics(double[][] xData, double[][] yData)
This is a static method that can be used to compute the statistics
regardless of the training class used to train the network
.
Computes statistics related to the error. In this table, the observed values are . The forecasted values are . The mean observed value is , where N is the number of observations and C is the number of classes per observation.
Index | Name | Formula |
0 | SSE | |
1 | RMS | |
2 | Laplacian | |
3 | Scaled Laplacian | |
4 | Max residual |
xData
- A double
matrix containing the input values.yData
- A double
array containing the observed
values.
double
array containing the above described
statistics.public abstract HiddenLayer createHiddenLayer()
HiddenLayer
in the Network
.
HiddenLayer
.public abstract double[] forecast(double[] x)
Network
's outputs
computed from the trained Network
.
x
- A double
array of values with the same length and
order as the training patterns used to train the
Network
.
double
array containing the forecasts for the
output Perceptron
s. Its length is equal to the
number of output Perceptron
s.public abstract double[][] getForecastGradient(double[] x)
x
- A double
array which specifies the input
values at which the gradient is to be evaluated.
double
array containing the gradient values.
The value of gradient[i][j]
is
, where
is the i-th output and
is the j-th weight.public abstract InputLayer getInputLayer()
InputLayer
object.
Network
InputLayer
.public abstract Link[] getLinks()
Link
objects in the
Network
.
Link
s associated with this
Network
.public abstract int getNumberOfInputs()
Network
inputs.
int
which contains the number of inputs.public abstract int getNumberOfLinks()
Network
Link
s among the
node
s.
int
which contains the number of Link
s in
the Network
.public abstract int getNumberOfOutputs()
Network
output Perceptron
s.
int
which contains the number of outputs.public abstract int getNumberOfWeights()
Network
.
int
which contains the number of weights
associated with this Network
.public abstract OutputLayer getOutputLayer()
OutputLayer
.
Network
OutputLayer
.public abstract Perceptron[] getPerceptrons()
Perceptron
s in the
Network
.
Perceptron
s associated with this
Network
.public abstract double[] getWeights()
double
array containing the weights
associated with Network
Link
s.public abstract void setWeights(double[] weights)
weights
- A double
array which specifies the weights
to be associated with Network
Link
s.
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JMSLTM Numerical Library 4.0 | ||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |