Description Usage Arguments Details Value Author(s) See Also Examples
The Cross-Validation of Classification and Regression models using Partial Least Squares
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xtr |
A data frame or a matrix of predictors. |
ytr |
A response vector. If a factor, classification is assumed, otherwise regression is assumed. |
cv.fold |
The fold, the defalut is 5. |
maxcomp |
Maximum number of components included within the models, if not specified, default is the variable (column) numbers in x. |
This function performs k-fold cross validation for partial least squares regression and classification.
the retrun a list containing four components:
plspred
- the predicted values of the input data based on cross-validation
Error
- error for all samples
RMSECV
- Root Mean Square Error for cross-validation
Q2
- R2 for cross-validation
Min-feng Zhu <wind2zhu@163.com>
See rf.cv
for the Cross-Validation of Classification and
Regression models using Random Forest
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