@vijaypalmanit wrote:
can someone please explain how does repeated cv works and what are all these parameters marked red in caret package, I am really very confused in all these parameters
library(caret) # load the dataset data(iris) # prepare training scheme control <- trainControl(method="repeatedcv", number=10, repeats=5) # train the model model <- train(Species~., data=iris, method="lvq", trControl=control, tuneLength=5) # summarize the model print(model)Output :
> print(model) Learning Vector Quantization 150 samples 4 predictor 3 classes: 'setosa', 'versicolor', 'virginica' No pre-processing Resampling: Cross-Validated (10 fold, repeated 5 times) Summary of sample sizes: 135, 135, 135, 135, 135, 135, ... Resampling results across tuning parameters: size k Accuracy Kappa 5 1 0.9506667 0.926 5 6 0.9466667 0.920 5 11 0.9440000 0.916 5 16 0.9440000 0.916 5 21 0.9480000 0.922 6 1 0.9493333 0.924 6 6 0.9506667 0.926 6 11 0.9453333 0.918 6 16 0.9520000 0.928 6 21 0.9573333 0.936 7 1 0.9453333 0.918 7 6 0.9573333 0.936 7 11 0.9453333 0.918 7 16 0.9440000 0.916 7 21 0.9426667 0.914 8 1 0.9600000 0.940 8 6 0.9573333 0.936 8 11 0.9493333 0.924 8 16 0.9586667 0.938 8 21 0.9586667 0.938 10 1 0.9573333 0.936 10 6 0.9533333 0.930 10 11 0.9626667 0.944 10 16 0.9600000 0.940 10 21 0.9520000 0.928
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