Since I'm new to machine learning and I'm trying to build the model using caret package available in R.
I have a small confusion when using repeated cv method. Resampling output shows desired parameters which has highest accuracy. I did not clearly understand this part.
Below is my result when building Knn model for iris data set.
k-Nearest Neighbors
105 samples
4 predictor
3 classes: 'setosa', 'versicolor', 'virginica'
Pre-processing: centered (4), scaled (4)
Resampling: Cross-Validated (10 fold, repeated 3 times)
Summary of sample sizes: 95, 95, 94, 93, 94, 93, ...
Resampling results across tuning parameters:
k Accuracy Kappa
5 0.9476263 0.9211025
7 0.9379293 0.9066532
9 0.9278620 0.8914058
Accuracy was used to select the optimal model using the largest value.
The final value used for the model was k = 5
question: How are the different k values are selected?
