| knnreg {caret} | R Documentation |
$k$-nearest neighbour clasregressionsification that can return the average value for the neighbours.
## Default S3 method: knnreg(x, ...) ## S3 method for class 'formula': knnreg(formula, data, subset, na.action, k = 5, ...) ## S3 method for class 'matrix': knnreg(x, y, k = 5, ...) ## S3 method for class 'data.frame': knnreg(x, y, k = 5, ...) knnregTrain(train, test, y, k = 5, use.all=TRUE)
formula |
a formula of the form lhs ~ rhs where lhs
is the response variable and rhs a set of
predictors. |
data |
optional data frame containing the variables in the model formula. |
subset |
optional vector specifying a subset of observations to be used. |
na.action |
function which indicates what should happen when
the data contain NAs. |
k |
number of neighbours considered. |
x |
a matrix or data frame of training set predictors. |
y |
a numeric vector of outcomes. |
... |
additional parameters to pass to knnregTrain. |
train |
matrix or data frame of training set cases. |
test |
matrix or data frame of test set cases. A vector will be interpreted as a row vector for a single case. |
use.all |
controls handling of ties. If true, all distances equal to the kth
largest are included. If false, a random selection of distances
equal to the kth is chosen to use exactly k neighbours. |
knnreg is similar to ipredknn
and knnregTrain is a modification of knn. The underlying
C code from the class pacakge has been modifed to return average outcome.
An object of class knnreg. See predict.knnreg.
knn by W. N. Venables and B. D. Ripley and
ipredknn by
Torsten.Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>,
modifications by Max Kuhn and Chris Keefer
data(BloodBrain) inTrain <- createDataPartition(logBBB, p = .8)[[1]] trainX <- bbbDescr[inTrain,] trainY <- logBBB[inTrain] testX <- bbbDescr[-inTrain,] testY <- logBBB[-inTrain] fit <- knnreg(trainX, trainY, k = 3) plot(testY, predict(fit, testX))