Performing cross-validation with the e1071 package
Besides implementing a loop
function to perform the k-fold cross-validation, you can use the tuning
function (for example, tune.nnet
, tune.randomForest
, tune.rpart
, tune.svm
, and tune.knn
.) within the e1071
package to obtain the minimum error value. In this recipe, we will illustrate how to use tune.svm
to perform the 10-fold cross-validation and obtain the optimum classification model.
Getting ready
In this recipe, we continue to use the telecom churn
dataset as the input data source to perform 10-fold cross-validation.
How to do it...
Perform the following steps to retrieve the minimum estimation error using cross-validation:
- Apply
tune.svm
on the training dataset,trainset
, with the 10-fold cross-validation ...
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