KMeansModel: KMeansModel

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

Description

Function finding the Bayesian Model given the KMeans clustering algorithm

Usage

KMeansModel(train, trainpharmat, num_clusters, cl)

Arguments

train	matrix of train features
trainpharmat	matrix of training of side_effects
num_clusters	number of clusters desired
cl	results of the KMeans model clustering function

Value

A Bayesian matrix of model for predictions, given the KMeans clustering

Examples

#First call the KMeans function and obtain cl (list of clusters)
#train is the feature matrix of train
#trainpharmat is the side effect matrix of train
#A<-KMeansModel(train,trainpharmat,4,cl)

Example output

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