# logp

Log unconditional probability density for discriminant analysis classifier

## Syntax

lp = logp(obj,Xnew)

## Description

lp = logp(obj,Xnew) returns the log of the unconditional probability density of each row of Xnew, computed using the discriminant analysis model obj.

## Input Arguments

 obj Discriminant analysis classifier, produced using fitcdiscr. Xnew Matrix where each row represents an observation, and each column represents a predictor. The number of columns in Xnew must equal the number of predictors in obj.

## Output Arguments

 lp Column vector with the same number of rows as Xnew. Each entry is the logarithm of the unconditional probability density of the corresponding row of Xnew.

## Examples

expand all

Construct a discriminant analysis classifier for Fisher's iris data, and examine its prediction for an average measurement.

Load Fisher's iris data and construct a default discriminant analysis classifier.

Mdl = fitcdiscr(meas,species);

Find the log probability of the discriminant model applied to an average iris.

logpAverage = logp(Mdl,mean(meas))
logpAverage = -1.7254