Description Usage Arguments Value See Also Examples
KNN Test The knn_test_function returns the labels for a test set using the k-Nearest Neighbors Clasification method.
1 | knn_test_function(dataset, test, distance, labels, k = 3)
|
dataset |
is a matrix with the features of the training set |
test |
is a matrix where the columns are the features of the test set |
distance |
is a nxn matrix with the distance between each observation of the test set and the training set |
labels |
is a nx1 vector with the labels of the training set |
k |
is from the numeric class and represent the number of neigbours to be use in the classifier. |
a k vector with the predicted labels for the test set.
1 2 3 4 5 6 7 8 9 | # Create Data for restaurant reviews
training <- matrix(rexp(600,1), ncol=2)
test <- matrix(rexp(200,1), ncol=2)
# Label "Good", "Bad", "Average"
labelsExample <- c(rep("Good",100), rep("Bad",100), rep("Average",100))
# Distance Matrix
distanceExample<-Distance_for_KNN_test(test, training)
# KNN
knn_test_function(training, test, distanceExample,labelsExample, k = 3)
|
[1] "Good" "Bad" "Bad" "Good" "Good" "Good" "Good"
[8] "Average" "Average" "Good" "Bad" "Average" "Bad" "Good"
[15] "Good" "Average" "Good" "Bad" "Average" "Average" "Bad"
[22] "Bad" "Average" "Bad" "Good" "Good" "Bad" "Average"
[29] "Bad" "Average" "Average" "Good" "Good" "Good" "Average"
[36] "Bad" "Bad" "Bad" "Average" "Good" "Bad" "Average"
[43] "Good" "Average" "Bad" "Average" "Bad" "Good" "Bad"
[50] "Good" "Bad" "Good" "Average" "Average" "Bad" "Good"
[57] "Bad" "Average" "Average" "Bad" "Average" "Average" "Average"
[64] "Average" "Bad" "Good" "Average" "Average" "Average" "Bad"
[71] "Average" "Average" "Bad" "Bad" "Average" "Bad" "Average"
[78] "Average" "Good" "Good" "Average" "Bad" "Average" "Average"
[85] "Good" "Good" "Bad" "Good" "Bad" "Good" "Average"
[92] "Average" "Good" "Average" "Bad" "Bad" "Average" "Bad"
[99] "Good" "Good"
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.