Class prediction based on microarray data and clinical parameters

Documentation for package ‘MAclinical’ version 1.0-2

generate.learningsets	Generating learning sets
logistic_z	Class prediction based on logistic regression using clinical parameters only
plsrf_x	Classification based on PLS dimension reduction and random forests using microarray data only
plsrf_xz	Classification based on PLS dimension reduction and random forests using both clinical and microarray predictors
plsrf_xz_pv	Classification based on pre-validated PLS dimension reduction and random forests using both clinical and microarray predictors
plsrf_x_pv	Classification based on pre-validated PLS dimension reduction and random forests using microarray data only
rf_z	Class prediction based on random forests using clinical parameters only
simuldatacluster_list	Simulating data
simuldata_list	Simulating data
svm_x	Classification based on support vector machines using microarray data only
testclass	Evaluating a classification method based on several learning subsets
testclass_simul	Evaluating a classification method based on simulated data