Package weka.estimators
Class NormalEstimator
- java.lang.Object
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- weka.estimators.Estimator
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- weka.estimators.NormalEstimator
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- All Implemented Interfaces:
java.io.Serializable,java.lang.Cloneable,Aggregateable<NormalEstimator>,CapabilitiesHandler,CapabilitiesIgnorer,OptionHandler,RevisionHandler,IncrementalEstimator
public class NormalEstimator extends Estimator implements IncrementalEstimator, Aggregateable<NormalEstimator>
Simple probability estimator that places a single normal distribution over the observed values.- Version:
- $Revision: 9785 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description NormalEstimator(double precision)Constructor that takes a precision argument.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description voidaddValue(double data, double weight)Add a new data value to the current estimator.NormalEstimatoraggregate(NormalEstimator toAggregate)Aggregate an object with this onevoidfinalizeAggregation()Call to complete the aggregation process.CapabilitiesgetCapabilities()Returns default capabilities of the classifier.doublegetMean()Return the value of the mean of this normal estimator.doublegetPrecision()Return the value of the precision of this normal estimator.doublegetProbability(double data)Get a probability estimate for a valuejava.lang.StringgetRevision()Returns the revision string.doublegetStdDev()Return the value of the standard deviation of this normal estimator.doublegetSumOfWeights()Return the sum of the weights for this normal estimator.static voidmain(java.lang.String[] argv)Main method for testing this class.static voidtestAggregation()java.lang.StringtoString()Display a representation of this estimator-
Methods inherited from class weka.estimators.Estimator
addValues, addValues, addValues, addValues, buildEstimator, buildEstimator, clone, debugTipText, doNotCheckCapabilitiesTipText, equals, forName, getDebug, getDoNotCheckCapabilities, getOptions, listOptions, makeCopies, makeCopy, setDebug, setDoNotCheckCapabilities, setOptions, testCapabilities
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Constructor Detail
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NormalEstimator
public NormalEstimator(double precision)
Constructor that takes a precision argument.- Parameters:
precision- the precision to which numeric values are given. For example, if the precision is stated to be 0.1, the values in the interval (0.25,0.35] are all treated as 0.3.
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Method Detail
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addValue
public void addValue(double data, double weight)Add a new data value to the current estimator.- Specified by:
addValuein interfaceIncrementalEstimator- Overrides:
addValuein classEstimator- Parameters:
data- the new data valueweight- the weight assigned to the data value
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getProbability
public double getProbability(double data)
Get a probability estimate for a value- Specified by:
getProbabilityin classEstimator- Parameters:
data- the value to estimate the probability of- Returns:
- the estimated probability of the supplied value
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toString
public java.lang.String toString()
Display a representation of this estimator- Overrides:
toStringin classjava.lang.Object
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getCapabilities
public Capabilities getCapabilities()
Returns default capabilities of the classifier.- Specified by:
getCapabilitiesin interfaceCapabilitiesHandler- Overrides:
getCapabilitiesin classEstimator- Returns:
- the capabilities of this classifier
- See Also:
Capabilities
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getMean
public double getMean()
Return the value of the mean of this normal estimator.- Returns:
- the mean
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getStdDev
public double getStdDev()
Return the value of the standard deviation of this normal estimator.- Returns:
- the standard deviation
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getPrecision
public double getPrecision()
Return the value of the precision of this normal estimator.- Returns:
- the precision
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getSumOfWeights
public double getSumOfWeights()
Return the sum of the weights for this normal estimator.- Returns:
- the sum of the weights
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classEstimator- Returns:
- the revision
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aggregate
public NormalEstimator aggregate(NormalEstimator toAggregate) throws java.lang.Exception
Description copied from interface:AggregateableAggregate an object with this one- Specified by:
aggregatein interfaceAggregateable<NormalEstimator>- Parameters:
toAggregate- the object to aggregate- Returns:
- the result of aggregation
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java.lang.Exception- if the supplied object can't be aggregated for some reason
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finalizeAggregation
public void finalizeAggregation() throws java.lang.ExceptionDescription copied from interface:AggregateableCall to complete the aggregation process. Allows implementers to do any final processing based on how many objects were aggregated.- Specified by:
finalizeAggregationin interfaceAggregateable<NormalEstimator>- Throws:
java.lang.Exception- if the aggregation can't be finalized for some reason
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testAggregation
public static void testAggregation()
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main
public static void main(java.lang.String[] argv)
Main method for testing this class.- Parameters:
argv- should contain a sequence of numeric values
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