CODEWITHSUNDEEP
rclassificationknn
MCL94
MCL94

Reputation: 21

adjusting the K in knn train() command in R

I'm trying to classify with the knn algorithm. My question is how do I adjust the number of neighbors the algorithm uses?

For example, I want to use 3, 9 and 12?
How do I adjust this in the command? 

species_knn = train(species ~., method= "knn", data = species, trControl=trainControl(method = 'cv', number = 3))

Upvotes: 2

Views: 1655

Answers (1)

missuse
missuse

Reputation: 19716

Here is an example of grid search using iris data:

library(caret)

construct a grid of hyper parameters which you would like to tune: 

grid = expand.grid(k = c(3, 9, 12)) #in this case data.frame(k = c(3, 9, 12)) will do

provide the grid in tuneGrid argument:

species_knn = train(Species ~., method= "knn",
                    data = iris,
                    trControl = trainControl(method = 'cv',
                                             number = 3,
                                             search = "grid"),
                     tuneGrid = grid)
species_knn$results
#output
    k  Accuracy     Kappa AccuracySD      KappaSD
1  3 0.9666667 0.9499560 0.02309401 0.0346808964
2  9 0.9600000 0.9399519 0.00000000 0.0000416525
3 12 0.9533333 0.9299479 0.01154701 0.0173066504

Here is a list of all available models and hyper parameters.

Upvotes: 2

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