I have a binary matrix between 2 variables. I would like to know if there is a way to cluster the binary matrix in R. If so, which algorithm should I be using?
The matrix looks like this
hobby1 hobby2 hobby3 hobby4
person1 1 0 0 1
person2 0 1 0 1
person3 1 1 1 0
person4 0 1 1 1
So clustering those persons by the most common hobbies they have. What is the best method to do it?
Thanks
How about crossprod() and reshape2::melt():
# CREATE THE MATRIX
m.h<-(matrix(sample(0:1,200,T),nrow=20))
# CREATE CROSS_PRODUCT
m.cross<-matrix(unlist(lapply(1:nrow(m.h),function(x)crossprod(m.h[x,],t(m.h)))),nrow=nrow(m.h),byrow=T)
# USE reshape2 to melt/flatten the data
require(reshape2)
m.long<-melt(m.cross)
m.long[order(m.long$value,factor(m.long$Var2),factor(m.long$Var1)),]
require(ggplot2)
ggplot(m.long)+
geom_tile(aes(Var1,Var2,fill=value))+
geom_text(aes(Var1,Var2,label=value))+
theme(axis.text.x = element_text(angle = 90, hjust = 1))+
scale_fill_gradient(low="yellow",high="red") +
scale_x_discrete(breaks = 1:nrow(m.h), labels=unlist(lapply(1:nrow(m.h),function(x)paste0("Person ",x)))) +
scale_y_discrete(breaks = 1:nrow(m.h), labels=unlist(lapply(1:nrow(m.h),function(x)paste0("Person ",x)))) +
coord_cartesian(xlim=c(0,nrow(m.h)+1),ylim=c(0,nrow(m.h)+1))

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