`mnlfactory`

Construct a multinomial logistic distribution (MaxEnt classifier)

**Syntax**

D = mnlfactory(datadim, num) D = mnlfactory(datadim)

**Description**

`D = mnlfactory(datadim, num)` returns a structure representing a multi-nomial logit distribution. `datadim` is the dimension of input space and `num` is the number of labels.

`D = mnlfactory(datadim)` is the same as above with `num = 2`, this case equals usual logistic regression.

**Distribution Parameters**

(`W``(num - 1)-by-datadim`matrix) : A matrix containing weights from input space to`num`classifier

**Probability Density Function**

The distribution has the following density:

`name`

See distribution structure common members.

`M`

See distribution structure common members.

`num`

Number of components

**Syntax**

num = D.num()

`dim`

See distribution structure common members.

`datadim`

See distribution structure common members.

`llvec`

See distribution structure common members.

`ll`

See distribution structure common members.

`llgrad`

See distribution structure common members.

`llgraddata`

See distribution structure common members.

`pdf`

See distribution structure common members.

`sample`

See distribution structure common members.

`randparam`

See distribution structure common members.

`init`

See distribution structure common members.

`penalizerparam`

See distribution structure common members.

`penalizercost`

See distribution structure common members.

`penalizergrad`

See distribution structure common members.

`sumparam`

See distribution structure common members.

`scaleparam`

See distribution structure common members.

`sumgrad`

See distribution structure common members.

`scalegrad`

See distribution structure common members.

`entropy`

See distribution structure common members.

`kl`

See distribution structure common members.

`AICc`

See distribution structure common members.

`BIC`

See distribution structure common members.