java.lang.Object
- weka.estimators.Estimator
- - weka.estimators.NormalEstimator

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, IncrementalEstimator
```
public class NormalEstimator
extends Estimator
implements IncrementalEstimator
```
Simple probability estimator that places a single normal distribution over the observed values.

Version:

$Revision: 5540 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor Description

NormalEstimator(double precision)
Constructor that takes a precision argument.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`addValue(double data, double weight)`	Add a new data value to the current estimator.
`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.
`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, equals, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions, testCapabilities

Methods inherited from class java.lang.Object
getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - 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
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain a sequence of numeric values

Class NormalEstimator

Constructor Summary

Method Summary

Methods inherited from class weka.estimators.Estimator

Methods inherited from class java.lang.Object

Constructor Detail

NormalEstimator

Method Detail

addValue

getProbability

toString

getCapabilities

getMean

getStdDev

getPrecision

getSumOfWeights

getRevision

main