modelLookup
Descriptions Of Models Available in train()
This function enumerates the parameters and characteristics for models used
by train
- Keywords
- utilities
Usage
modelLookup(model = NULL)
Details
One characteristic listed in the output is whether or not sub-models can be used for prediction. For example,
if a PLS model is fit with X components, PLS models with These types of tuning parameters are defined as "sequential" parameters since one value can be used to derive a
sequences of predictions. Examples of model codes that include sequential tuning parameters are; blackboost
,
ctree
, earth
, enet
, foba
, gamboost
, gbm
, glmboost
,
glmnet
, lars
, lars2
, lasso
, logitBoost
, pam
, partDSA
,
pcr
, pls
, relaxo
, rpart
, scrda
and superpc
.
Value
- a data frame with columns
model a character string for the model code parameter the tuning parameter name label a tuning parameter label (used in plots) seq a logical; can sub-models be used to decrease training time (see the Details section) forReg a logical; can the model be used for regression? forClass a logical; can the model be used for classification? probModel a logical; does the model produce class probabilities?
See Also
Examples
modelLookup()
modelLookup("gbm")
Community examples
Actually example doesn't work for me this one works: ```r checkInstall(getModelInfo("OneR")[["OneR"]][["library"]]) ```