R: L1 shrinkage of the predictor variables in a GBM

shrink.gbm {gbm} | R Documentation

## L1 shrinkage of the predictor variables in a GBM

### Description

Performs recursive shrinkage in each of the trees in a GBM fit using different shrinkage parameters for each variable.

### Usage

    shrink.gbm(object,
               n.trees,
               lambda = rep(10, length(object$var.names)),
               ...)

### Arguments

`object` | A `gbm.object`
`n.trees` | the number of trees to use
`lambda` | a vector with length equal to the number of variables containing the shrinkage parameter for each variable
`...` | other parameters (ignored)

### Details

This function is currently experimental. Used in conjunction with a gradient ascent search for inclusion of variables.

### Value

`predF` | Predicted values from the shrunken tree
`objective` | The value of the loss function associated with the predicted values
`gradient` | A vector with length equal to the number of variables containing the derivative of the objective function with respect to beta, the logit transform of the shrinkage parameter for each variable

### Warning

This function is experimental.

### Author(s)

Greg Ridgeway gregridgeway@gmail.com

### References

Hastie, T. J., and Pregibon, D. Shrinking Trees. AT&T Bell Laboratories Technical Report (March 1990).

### See Also

`shrink.gbm.pred`, `gbm`

[Package gbm version 2.1.3 Index]