k-nearest neighbor regression
1 |
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. If not supplied, cross-validataion will be done. |
y |
reponse of each observation in the training set. |
k |
number of neighbours considered. |
algorithm |
nearest neighbor search algorithm. |
If test is not supplied, Leave one out cross-validation is performed and R-square is the predicted R-square.
knn.reg
returns an object of class
"knnReg"
or "knnRegCV"
if test
data is not supplied.
The returnedobject is a list containing at least the following components:
call |
the match call. |
k |
number of neighbours considered. |
n |
number of predicted values, either equals test size or train size. |
pred |
a vector of predicted values. |
residuals |
predicted residuals. |
PRESS |
the sums of squares of the predicted residuals. |
R2Pred |
predicted R-square. |
The code for “VR” nearest neighbor searching is taken from class
source
Shengqiao Li. To report any bugs or suggestions please email: shli@stat.wvu.edu.
knn
.
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Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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