![caret models caret models](https://image.slidesharecdn.com/odscbos2015maxkhun-150601094910-lva1-app6892/95/the-caret-package-is-a-unified-interface-to-a-large-number-of-predictive-model-functions-in-r-5-638.jpg)
The combination with the optimal resampling statistic is chosen as the final model and the entire training set is used to fit a final model.Ī variety of models are currently available. Across each data set, the performance of held-out samples is calculated and the mean and standard deviation is summarized for each combination. For particular model, a grid of parameters (if any) is created and the model is trained on slightly different data for each candidate combination of tuning parameters. maximize a logical recycled from the function arguments.ĭetails train can be used to tune models by picking the complexity parameters that are associated with the optimal resampling statistics.perfNames a character vector of performance metrics that are produced by the summary function.The returnResamp argument of trainControlĬontrols how much of the resampled results are saved. If leave-one-outĬross-validation or out-of-bag estimation methods are requested, resample A data frame with columns for each performance.finalModel an fit object using the best parameters.trControl the list of control parameters.metric a string that specifies what summary metric will be used to select the optimal model.call the (matched) function call with dots expanded.
![caret models caret models](https://image.slidesharecdn.com/maxcaretnycpa-110613111417-phpapp02/95/the-caret-package-a-unified-interface-for-predictive-models-27-728.jpg)
results a data frame the training error rate and values of the tuning parameters.
![caret models caret models](https://www.rstudio.com/wp-content/uploads/2015/01/caret-cheatsheet.png)