knnreg {caret} | R Documentation |
$k$-nearest neighbour regression that can return the average value for the neighbours.
knnreg(x, ...)
## 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, ...)
## S3 method for class 'knnreg'
print(x, ...)
knnregTrain(train, test, y, k = 5, use.all = TRUE)
x |
a matrix or data frame of training set predictors. |
... |
additional parameters to pass to |
formula |
a formula of the form |
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 |
k |
number of neighbours considered. |
y |
a numeric vector of outcomes. |
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 |
knnreg
is similar to ipredknn
and
knnregTrain
is a modification of knn
. The
underlying C code from the class
package has been modified 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))