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java.lang.Objectorg.encog.ml.train.strategy.RequiredImprovementStrategy
public class RequiredImprovementStrategy
The reset strategy will reset the weights if the neural network fails to improve by the specified amount over a number of cycles.
| Constructor Summary | |
|---|---|
RequiredImprovementStrategy(double required,
double threshold,
int cycles)
Construct a reset strategy. |
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RequiredImprovementStrategy(double required,
int cycles)
Construct a reset strategy. |
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RequiredImprovementStrategy(int cycles)
Reset if there is not at least a 1% improvement for 5 cycles. |
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| Method Summary | |
|---|---|
void |
init(MLTrain train)
Initialize this strategy. |
void |
postIteration()
Called just after a training iteration. |
void |
preIteration()
Called just before a training iteration. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public RequiredImprovementStrategy(double required,
int cycles)
required - The required error rate.cycles - The number of cycles to reach that rate.
public RequiredImprovementStrategy(double required,
double threshold,
int cycles)
required - The required error rate.threshold - The accepted threshold, don't reset if error is below this.cycles - The number of cycles to reach that rate.public RequiredImprovementStrategy(int cycles)
cycles - | Method Detail |
|---|
public void init(MLTrain train)
init in interface Strategytrain - The training algorithm.public void postIteration()
postIteration in interface Strategypublic void preIteration()
preIteration in interface Strategy
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