Random KNN Classification and Regression

Documentation for package ‘rknn’ version 1.2-1

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