weka.estimators

Class NormalEstimator

java.lang.Object

weka.estimators.Estimator

weka.estimators.NormalEstimator

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: 15521 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NormalEstimator() No-arg constructor needed to make WEKA's forName() work.
NormalEstimator(double precision) Constructor that takes a precision argument.

Method Summary

Modifier and Type	Method and Description
void	addValue(double data, double weight) Add a new data value to the current estimator.
NormalEstimator	aggregate(NormalEstimator toAggregate) Aggregate an object with this one
void	finalizeAggregation() Call to complete the aggregation process.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
double	getMean() Return the value of the mean of this normal estimator.
double	getPrecision() Return the value of the precision of this normal estimator.
double	getProbability(double data) Get a probability estimate for a value
java.lang.String	getRevision() Returns the revision string.
double	getStdDev() Return the value of the standard deviation of this normal estimator.
double	getSumOfWeights() Return the sum of the weights for this normal estimator.
static void	main(java.lang.String[] argv) Main method for testing this class.
static void	testAggregation()
java.lang.String	toString() 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

Methods inherited from class java.lang.Object

getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

NormalEstimator

public NormalEstimator()

No-arg constructor needed to make WEKA's forName() work. Uses precision of 0.01.

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.

Method Detail

addValue

public void addValue(double data,
                     double weight)

Add a new data value to the current estimator.

Specified by:

addValue in interface IncrementalEstimator

Overrides:

addValue in class Estimator

Parameters:

data - the new data value

weight - the weight assigned to the data value

getProbability

public double getProbability(double data)

Get a probability estimate for a value

Specified by:

getProbability in class Estimator

Parameters:

data - the value to estimate the probability of

Returns:

the estimated probability of the supplied value

toString

public java.lang.String toString()

Display a representation of this estimator

Overrides:

toString in class java.lang.Object

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class Estimator

Returns:

the capabilities of this classifier

See Also:

Capabilities

getMean

public double getMean()

Return the value of the mean of this normal estimator.

Returns:

the mean

getStdDev

public double getStdDev()

Return the value of the standard deviation of this normal estimator.

Returns:

the standard deviation

getPrecision

public double getPrecision()

Return the value of the precision of this normal estimator.

Returns:

the precision

getSumOfWeights

public double getSumOfWeights()

Return the sum of the weights for this normal estimator.

Returns:

the sum of the weights

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class Estimator

Returns:

the revision

aggregate

public NormalEstimator aggregate(NormalEstimator toAggregate)
                          throws java.lang.Exception

Description copied from interface: Aggregateable

Aggregate an object with this one

Specified by:

aggregate in interface Aggregateable<NormalEstimator>

Parameters:

toAggregate - the object to aggregate

Returns:

the result of aggregation

Throws:

java.lang.Exception - if the supplied object can't be aggregated for some reason

finalizeAggregation

public void finalizeAggregation()
                         throws java.lang.Exception

Description copied from interface: Aggregateable

Call to complete the aggregation process. Allows implementers to do any final processing based on how many objects were aggregated.

Specified by:

finalizeAggregation in interface Aggregateable<NormalEstimator>

Throws:

java.lang.Exception - if the aggregation can't be finalized for some reason

testAggregation

public static void testAggregation()

main

public static void main(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - should contain a sequence of numeric values