# knnreg

##### k-Nearest Neighbour Regression

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

- Keywords
- multivariate

##### Usage

`knnreg(x, ...)`# S3 method for default
knnreg(x, ...)

# S3 method for formula
knnreg(formula, data, subset, na.action, k = 5, ...)

# S3 method for matrix
knnreg(x, y, k = 5, ...)

# S3 method for data.frame
knnreg(x, y, k = 5, ...)

# S3 method for knnreg
print(x, ...)

knnregTrain(train, test, y, k = 5, use.all = TRUE)

##### Arguments

- x
a matrix or data frame of training set predictors.

- ...
additional parameters to pass to

`knnregTrain`

.- 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

`NA`

s.- 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

`k`

th largest are included. If false, a random selection of distances equal to the`k`

th 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`

package has been modified to return
average outcome.

##### Value

An object of class `knnreg`

. See `predict.knnreg`

.

##### Examples

```
# NOT RUN {
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 6.0-85, License: GPL (>= 2)*