DrugClustKMeans: DrugClustKMeans

In DrugClust: Implementation of a Machine Learning Framework for Predicting Drugs Side Effects

Description

Function Implementing DrugClust with KMeans algorithm

Usage

DrugClustKMeans(num_folds, num_clusters, num_iterations, features, side_effects)

Arguments

num_folds	number of folds
num_clusters	number of clusters
num_iterations	number of iterations
features	features matrix
side_effects	side_effects matrix

Value

(list(AUCFinal,AUPRFinal)) first value is the mean AUC on the various folders, second value is the mean AUPR on the various folders

Examples

# num_folds=3
# num_clusters=4
# num_iterations= 5
#features is the features matrix (see InitFeatures function)
# side effects is the matrix containing side effects (see InitSideEffects function)
#result<-DrugClustKMeans(num_folds,num_clusters,num_iterations,features,side_effects)

DrugClust documentation built on May 2, 2019, 11:06 a.m.