R: Random KNN Classification and Regression

# Random KNN Classification and Regression

## Documentation for package ‘rknn’ version 1.2-1

- DESCRIPTION file.

## Help Pages

rknn-package | Random KNN Classification and Regression
bestset | Extract the Best Subset of Feature from Selection Process
confusion | Classification Confusion Matrix and Accuracy
confusion2acc | Classification Confusion Matrix and Accuracy
cv.coef | Coefficient of Variation
eta | Coverage Probability
fitted.rknn | Extract Model Fitted Values
lambda | Compute Number of Silent Features
normalize.decscale | Data Normalization
normalize.sigmoidal | Data Normalization
normalize.softmax | Data Normalization
normalize.unit | Data Normalization
plot.rknnBeg | Plot Function for Recursive Backward Elimination Feature Selection
plot.rknnBel | Plot Function for Recursive Backward Elimination Feature Selection
plot.rknnSupport | Plot Function for Support Criterion
prebestset | Extract the Best Subset of Feature from Selection Process
predicted | Prediced Value From a Linear Model
PRESS | Predicted Residual Sum of Squares
print.rknn | Print method for Random KNN
print.rknnBE | Print Method for Recursive Backward Elimination Feature Selection
print.rknnSupport | Print Method for Random KNN Support Criterion
r | Choose number of KNNs
rknn | Random KNN Classification and Regression
rknn.cv | Random KNN Classification and Regression
rknnBeg | Backward Elimination Feature Selection with Random KNN
rknnBel | Backward Elimination Feature Selection with Random KNN
rknnReg | Random KNN Classification and Regression
rknnRegSupport | Support Criterion
rknnSupport | Support Criterion
rsqp | Predicted R-square
varNotUsed | Features Used or Not Used in Random KNN
varUsed | Features Used or Not Used in Random KNN