public class SumSquaredErrorCostFunction extends AbstractParallelizableCostFunction
Modifier and Type | Class and Description |
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static class |
SumSquaredErrorCostFunction.Cache
Caches often-used values for the Cost Function
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static class |
SumSquaredErrorCostFunction.GradientPartialSSE
Partial result from the SSE gradient computation
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Constructor and Description |
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SumSquaredErrorCostFunction()
Creates a new instance of SumSquaredErrorCostFunction
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SumSquaredErrorCostFunction(java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>> dataset)
Creates a new instance of MeanSquaredErrorCostFunction
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Modifier and Type | Method and Description |
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SumSquaredErrorCostFunction |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
Vector |
computeParameterGradientAmalgamate(java.util.Collection<java.lang.Object> partialResults)
Amalgamates the linear components of the cost gradient function into a
single Vector.
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java.lang.Object |
computeParameterGradientPartial(GradientDescendable function)
Computes the partial (linear) component of the cost function gradient.
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java.lang.Double |
evaluateAmalgamate(java.util.Collection<java.lang.Object> partialResults)
Amalgamates the linear components of the cost function into a single
Double.
|
java.lang.Object |
evaluatePartial(Evaluator<? super Vector,? extends Vector> evaluator)
Computes the partial (linear) component of the cost function.
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java.lang.Double |
evaluatePerformance(java.util.Collection<? extends TargetEstimatePair<? extends Vector,? extends Vector>> data)
Evaluates the performance accuracy of the given estimates against the
given targets.
|
computeParameterGradient, evaluate
getCostParameters, setCostParameters, summarize
evaluatePerformance
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getCostParameters, setCostParameters
summarize
evaluatePerformance
public SumSquaredErrorCostFunction()
public SumSquaredErrorCostFunction(java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>> dataset)
dataset
- The dataset of examples to use to compute the error.public SumSquaredErrorCostFunction clone()
AbstractCloneableSerializable
Object
class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone()
to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil
may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone()
as the basis for your implementation.clone
in interface CostFunction<Evaluator<? super Vector,? extends Vector>,java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>>>
clone
in interface CloneableSerializable
clone
in class AbstractSupervisedCostFunction<Vector,Vector>
public java.lang.Object evaluatePartial(Evaluator<? super Vector,? extends Vector> evaluator)
ParallelizableCostFunction
evaluator
- Evaluator to compute the cost ofpublic java.lang.Double evaluateAmalgamate(java.util.Collection<java.lang.Object> partialResults)
ParallelizableCostFunction
partialResults
- Collection of partial (linear) resultspublic java.lang.Object computeParameterGradientPartial(GradientDescendable function)
ParallelizableCostFunction
function
- GradientDescendable to compute the gradient ofpublic Vector computeParameterGradientAmalgamate(java.util.Collection<java.lang.Object> partialResults)
ParallelizableCostFunction
partialResults
- Collection of partial (linear) gradient componentspublic java.lang.Double evaluatePerformance(java.util.Collection<? extends TargetEstimatePair<? extends Vector,? extends Vector>> data)
SupervisedPerformanceEvaluator
evaluatePerformance
in interface SupervisedPerformanceEvaluator<Vector,Vector,Vector,java.lang.Double>
evaluatePerformance
in class AbstractSupervisedCostFunction<Vector,Vector>
data
- The target-estimate pairs to use to evaluate performance.