rf_filter | R Documentation |
Fits a random forest model and ranks variables by variable importance.
rf_filter(
y,
x,
nfilter = NULL,
type = c("index", "names", "full"),
ntree = 1000,
mtry = ncol(x) * 0.2,
...
)
y |
Response vector |
x |
Matrix or dataframe of predictors |
nfilter |
Number of predictors to return. If |
type |
Type of vector returned. Default "index" returns indices, "names" returns predictor names, "full" returns a named vector of variable importance. |
ntree |
Number of trees to grow. See randomForest::randomForest. |
mtry |
Number of predictors randomly sampled as candidates at each split. See randomForest::randomForest. |
... |
Optional arguments passed to randomForest::randomForest. |
This filter uses the randomForest()
function from the randomForest
package. Variable importance is calculated using the
randomForest::importance function, specifying type 1 = mean decrease in
accuracy. See randomForest::importance.
Integer vector of indices of filtered parameters (type = "index") or
character vector of names (type = "names") of filtered parameters. If
type
is "full"
a named vector of variable importance is returned.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.