R: Filter features by thresholding filter values.

filterFeatures {mlr}

R Documentation

Filter features by thresholding filter values.

Description

First, calls generateFilterValuesData. Features are then selected via select and val.

Usage

filterFeatures(task, method = "randomForestSRC_importance",
  fval = NULL, perc = NULL, abs = NULL, threshold = NULL,
  mandatory.feat = NULL, cache = FALSE, ...)

Arguments

`task`	(Task) The task.
`method`	(`character(1)`) See listFilterMethods. Default is “randomForestSRC_importance”.
`fval`	(FilterValues) Result of generateFilterValuesData. If you pass this, the filter values in the object are used for feature filtering. `method` and `...` are ignored then. Default is `NULL` and not used.
`perc`	(`numeric(1)`) If set, select `perc`*100 top scoring features. `perc = 1` means to select all features.`Mutually exclusive with arguments`abs`and`threshold'.
`abs`	(`numeric(1)`) If set, select `abs` top scoring features. Mutually exclusive with arguments `perc` and `threshold`.
`threshold`	(`numeric(1)`) If set, select features whose score exceeds `threshold`. Mutually exclusive with arguments `perc` and `abs`.
`mandatory.feat`	(character) Mandatory features which are always included regardless of their scores
`cache`	(`character(1)` \| logical) Whether to use caching during filter value creation. See details.
`...`	(any) Passed down to selected filter method.

Value

Task.

Caching

If cache = TRUE, the default mlr cache directory is used to cache filter values. The directory is operating system dependent and can be checked with getCacheDir().
The default cache can be cleared with deleteCacheDir(). Alternatively, a custom directory can be passed to store the cache.