Knowledge discovery by accuracy maximization

Documentation for package ‘KODAMA’ version 0.0.1

classprob	Determines the Prevalence of Each Class
core	Maximization of Cross-Validateed Accuracy Methods
dinisurface	Ulisse Dini Data Set Generator
helicoid	Helicoid Data Set Generator
kfold	k-Fold Partitioning
KNN.CV	Cross-Validation with k-Nearest Neighbors Classifier.
knn.dist	Calculates the Distances for KNN Predictions
knn.predict	KNN Prediction Routine using Pre-Calculated Distances
knn.probability	KNN Prediction Probability Routine using Pre-Calculated Distances
KODAMA	Knowledge Discovery by Accuracy Maximization
lymphoma	Lymphoma Gene Expression Dataset
majority	Determines Majority Class
MetRef	Nuclear Magnetic Resonance Spectra of Urines
normalization	Normalization methods
PCA.CA.KNN.CV	Cross-Validation with PCA-CA-kNN.
PLS.SVM.CV	Cross-Validation with Support Vector Machine.
scaling	Scaling methods
spirals	Spirals Data Set Generator
swissroll	Swiss Roll Data Set Generator
transformy	Conversion Classification Vector to Matrix
USA	State of the Union Data Set