# predict

Predict labels using discriminant analysis classifier

## Description

`[`

also returns:`label`

,`score`

,`cost`

]
= predict(`Mdl`

,`X`

)

A matrix of classification scores (

`score`

) indicating the likelihood that a label comes from a particular class. For discriminant analysis, scores are posterior probabilities.A matrix of expected classification cost (

`cost`

). For each observation in`X`

, the predicted class label corresponds to the minimum expected classification cost among all classes.

## Examples

## Input Arguments

## Output Arguments

## More About

## Alternative Functionality

### Simulink Block

To integrate the prediction of a discriminant analysis classification model into
Simulink^{®}, you can use the ClassificationDiscriminant
Predict block in the Statistics and Machine Learning Toolbox™ library or a MATLAB^{®} Function block with the `predict`

function. For examples,
see Predict Class Labels Using ClassificationDiscriminant Predict Block and Predict Class Labels Using MATLAB Function Block.

When deciding which approach to use, consider the following:

If you use the Statistics and Machine Learning Toolbox library block, you can use the Fixed-Point Tool (Fixed-Point Designer) to convert a floating-point model to fixed point.

Support for variable-size arrays must be enabled for a MATLAB Function block with the

`predict`

function.If you use a MATLAB Function block, you can use MATLAB functions for preprocessing or post-processing before or after predictions in the same MATLAB Function block.

## Extended Capabilities

## Version History

**Introduced in R2011b**