org.openimaj.math.model.fit

Class SimpleModelFitting<I,D,M extends EstimatableModel<I,D>>

java.lang.Object

org.openimaj.math.model.fit.SimpleModelFitting<I,D,M>

Type Parameters:

I - type of independent data

D - type of dependent data

M - concrete type of model learned

All Implemented Interfaces:

ModelFitting<I,D,M>, RobustModelFitting<I,D,M>

public class SimpleModelFitting<I,D,M extends EstimatableModel<I,D>>
extends Object
implements RobustModelFitting<I,D,M>

Example robust fitting, that simply wraps the models estimate method. Inliers and outliers are estimated by verifying the model against the data.

Author:

Jonathon Hare

Constructor Summary

Constructors

Constructor and Description
SimpleModelFitting(M m, ResidualCalculator<I,D,M> errorModel, DistanceCheck dc) Creates a SimpleModelFitting object to fit data to a model
SimpleModelFitting(M m, ResidualCalculator<I,D,M> errorModel, double errorThreshold) Creates a SimpleModelFitting object to fit data to a model

Method Summary

Methods

Modifier and Type	Method and Description
boolean	fitData(List<? extends IndependentPair<I,D>> data) Attempt to fit the given data to the model.
List<? extends IndependentPair<I,D>>	getInliers()
M	getModel()
List<? extends IndependentPair<I,D>>	getOutliers()
int	numItemsToEstimate()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SimpleModelFitting

public SimpleModelFitting(M m,
                  ResidualCalculator<I,D,M> errorModel,
                  double errorThreshold)

Creates a SimpleModelFitting object to fit data to a model

Parameters:

m - model to fit data to

errorModel - the error model

errorThreshold - the error threshold

SimpleModelFitting

public SimpleModelFitting(M m,
                  ResidualCalculator<I,D,M> errorModel,
                  DistanceCheck dc)

Creates a SimpleModelFitting object to fit data to a model

Parameters:

m - model to fit data to

errorModel - the error model

dc - the error/distance check that determines whether a point is valid

Method Detail

getInliers

public List<? extends IndependentPair<I,D>> getInliers()

Specified by:

getInliers in interface RobustModelFitting<I,D,M extends EstimatableModel<I,D>>

Returns:

list of the inliers in the original data

getOutliers

public List<? extends IndependentPair<I,D>> getOutliers()

Specified by:

getOutliers in interface RobustModelFitting<I,D,M extends EstimatableModel<I,D>>

Returns:

list of the outliers in the original data

fitData

public boolean fitData(List<? extends IndependentPair<I,D>> data)

Description copied from interface: ModelFitting

Attempt to fit the given data to the model.

Specified by:

fitData in interface ModelFitting<I,D,M extends EstimatableModel<I,D>>

Parameters:

data - Data to be fitted

Returns:

true on success, false otherwise

getModel

public M getModel()

Specified by:

getModel in interface ModelFitting<I,D,M extends EstimatableModel<I,D>>

Returns:

the trained model object

numItemsToEstimate

public int numItemsToEstimate()

Specified by:

numItemsToEstimate in interface ModelFitting<I,D,M extends EstimatableModel<I,D>>

Returns:

The minimum number of observations required to estimate the model.