rknn-package: Random KNN Classification and Regression
Description
Random KNN Classification and RegressionDetails
ll{
Package: rknn
Type: Package
Version: 1.0
Date: 2012-04-22
Depends: R (>= 2.15.0), gmp, FNN
Suggests: Hmisc, Biobase, genefilter, golubEsets, chemometrics
Imports: class, FNN
License: GPL (>=2)
LazyLoad: yes
Packaged: 2012-04-2
}
Index:
PRESS Predicted Residual Sum of Squares
begKNN Backward Elimination Feature Selection with
Random KNN
bestset Extract the best subset of feature from
selection process
confusion Classification Confusion Matrix and Accuracy
cv.coef Coefficient of Variation
eta Coverage Probability
fitted.randomKNN Extract Model Fitted Values
knn.reg KNN Regression
knn.reg.cv KNN Regression Cross-Validation
lambda Compute Number of Silent Features
normalize.decscale Data Normalization
plot.begKNN Plot Function for Recursive Backward
Elimination Feature Selection
plot.supportRKNN Plot Function for Support Criterion
predicted Prediced Value From a Linear Model
print.KNNregcv Print Method for KNN Regression
Cross-validation
print.beKNN Print Method for Recursive Backward Elimination
Feature Selection
print.randomKNN Print method for Random KNN regression
cross-validation
print.supportRKNN Print Method for Random KNN Support Criterion
r Choose number of KNNs
randomKNN Random KNN Classification and Regression
rknn-package Random KNN Classification and Regression
rsqp Predicted R-square
supportRKNN Support Criterion
varUsed Features Used or Not Used in Random KNNReferences
Shengqiao Li, E James Harner and Donald A Adjeroh.
Random KNN feature selection - a fast and stable alternative to Random Forests.
BMC Bioinformatics 2011, 12:450. http://www.biomedcentral.com/1471-2105/12/450