knnreg

From caret v4.17 by Max Kuhn

k-Nearest Neighbour Regression

$k$-nearest neighbour clasregressionsification that can return the average value for the neighbours.

Keywords: multivariate

Usage

## S3 method for class 'default':
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)

Arguments

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.

Details

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.

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))

Documentation reproduced from package caret, version 4.17, License: GPL-2

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