## glmnetUtils 1.1.5

- Fix handling of non-factor categorical predictors (from R 4.0, data frames will not have character columns converted to factors by default). The practical impact of this should be minor.

## glmnetUtils 1.1.4

- Fix printout of
`glmnet.formula`

object.

## glmnetUtils 1.1.3

- Support relaxed (non-regularised) fits in
`glmnet.formula`

and `cv.glmnet.formula`

(requires glmnet 3.0 or later).
- Add a legend when plotting a
`cva.glmnet`

object.

## glmnetUtils 1.1.2

- Fixes a bug in the assignment of observations to crossvalidation folds in
`cva.glmnet`

. The impact is most serious for small datasets, where the number of observations per fold is relatively low. If you are using this function, itâ€™s highly recommended you update the package.

## glmnetUtils 1.1.1

- Fixes bug where
`nfolds`

argument was not being passed to `glmnet::cv.glmnet`

.

## glmnetUtils 1.1

- Now allows interaction and expression terms without requiring
`use.model.frame=TRUE`

. This works in an additive fashion, ie the formula `~ a + b:c + d*e`

is treated as consisting of three terms, `a`

, `b:c`

and `d*e`

each of which is processed independently of the others. A dot in the formula includes all main effect terms, ie `~ . + a:b + f(x)`

expands to `~ a + b + x + a:b + f(x)`

(assuming a, b and x are the only columns in the data). Note that a formula like `~ (a + b) + (c + d)`

will be treated as two terms, `a + b`

and `c + d`

.
- The call component of a
`glmnet`

/`cv.glmnet`

object that uses the original matrix/vector interface is now useful.
- You can now explicitly specify the vector of crossvalidation folds (for the inner loop over lambda) when calling
`cva.glmnet`

.
- Correctly handle non-syntactic factor variables in a formula.

## glmnetUtils 1.0.2