org.openimaj.math.model

Interface Model<I,D>

Type Parameters:

I - type of independent data

D - type of dependent data

All Known Subinterfaces:

EstimatableModel<I,D>, ImageClassificationModel<T>

All Known Implementing Classes:

AffineTransformModel, AffineTransformModel3d, FundamentalModel, GaussianVectorNaiveBayesModel, HistogramPatchModel, HistogramPixelModel, HomographyModel, LeastSquaresLinearModel, LinearRegression, MBFPatchClassificationModel, MBFPixelClassificationModel, NullModel, OrthotopePixelModel, PatchClassificationModel, PixelClassificationModel, RigidTransformModel3d, SimplePerceptron, SingleGaussianPixelModel, UnivariateGaussianNaiveBayesModel

public interface Model<I,D>

The Model interface defines a mathematical model which links dependent and independent variables. The model can be used to create predictions of the dependent variables given the independent ones.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Method Summary

Methods

Modifier and Type	Method and Description
D	predict(I data) Uses the model to predict dependent data from an independent value.

Method Detail

predict

D predict(I data)

Uses the model to predict dependent data from an independent value.

Parameters:

data - the data (independent variable)

Returns:

Dependent variable(s) predicted from the independent ones.