DrugClust (version 0.2)

KSeedsScores: KSeedsScores

Description

Function for obtaining the Bayesian prediction scores using KSeeds clustering

Usage

KSeedsScores(train, trainpharmat, num_clusters, Seed, s, clusters)

Arguments

train

train matrix of features

trainpharmat

train matrix of side effects

num_clusters

number of clusters desired

Seed

subset of the features matrix containing only the Seeds drugs

s

the seeds of the clusters

clusters

the list of clusters where the various drugs are

Value

A matrix containing prediction scores for each cluster

Examples

r <- 8
c <- 10
m0 <- matrix(0, r, c)
num_clusters=4
features<-apply(m0, c(1,2), function(x) sample(c(0,1),1))
#Generate a sample side effects binary matrix
r1 <- 8
c1 <- 10
m1 <- matrix(0, r1, c1)
side_effects<-apply(m1, c(1,2), function(x) sample(c(0,1),1))
s<-RandomSeedGenerator(num_clusters,nrow(features))
Seed<-SeedSelection(features,num_clusters,s)
clusters<-KSeedsClusters (features,num_clusters,Seed,s)
A<-KSeedsScores(features,side_effects,num_clusters,Seed,s,clusters)