# nLinearCoeffs

Number of nonzero linear coefficients

## Syntax

```ncoeffs = nLinearCoeffs(obj) ncoeffs = nLinearCoeffs(obj,delta) ```

## Description

`ncoeffs = nLinearCoeffs(obj)` returns the number of nonzero linear coefficients in the linear discriminant model `obj`.

`ncoeffs = nLinearCoeffs(obj,delta)` returns the number of nonzero linear coefficients for threshold parameter `delta`.

## Input Arguments

 `obj` Discriminant analysis classifier, produced using `fitcdiscr`. `delta` Scalar or vector value of the `Delta` parameter. See Gamma and Delta.

## Output Arguments

 `ncoeffs` Nonnegative integer, the number of nonzero coefficients in the discriminant analysis model `obj`. If you call `nLinearCoeffs` with a `delta` argument, `ncoeffs` is the number of nonzero linear coefficients for threshold parameter `delta`. If `delta` is a vector, `ncoeffs` is a vector with the same number of elements. If `obj` is a quadratic discriminant model, `ncoeffs` is the number of predictors in `obj`.

## Examples

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Find the number of nonzero coefficients in a discriminant analysis classifier for various `Delta` values.

Create a discriminant analysis classifier from the `fishseriris` data.

```load fisheriris obj = fitcdiscr(meas,species);```

Find the number of nonzero coefficients in `obj`.

`ncoeffs = nLinearCoeffs(obj)`
```ncoeffs = 4 ```

Find the number of nonzero coefficients for `delta` = 1, 2, 4, and 8.

```delta = [1 2 4 8]; ncoeffs = nLinearCoeffs(obj,delta)```
```ncoeffs = 4×1 4 4 3 0 ```

The `DeltaPredictor` property gives the values of `delta` where the number of nonzero coefficients changes.

`ncoeffs2 = nLinearCoeffs(obj,obj.DeltaPredictor)`
```ncoeffs2 = 4×1 4 3 1 2 ```