knnreg
From caret v6.070
by Max Kuhn
kNearest Neighbour Regression
$k$nearest neighbour regression that can return the average value for the neighbours.
 Keywords
 multivariate
Usage
"knnreg"(x, ...)
"knnreg"(formula, data, subset, na.action, k = 5, ...)
"knnreg"(x, y, k = 5, ...)
"knnreg"(x, y, k = 5, ...)
knnregTrain(train, test, y, k = 5, use.all=TRUE)
Arguments
 formula
 a formula of the form
lhs ~ rhs
wherelhs
is the response variable andrhs
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
NA
s.  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
k
th largest are included. If false, a random selection of distances equal to thek
th is chosen to use exactlyk
neighbours.
Details
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.
Value

An object of class
knnreg
. See predict.knnreg
.
Examples
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))
Community examples
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