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scenario
2012 Oct 08
1
Any better way of optimizing time for calculating distances in the mentioned scenario??
...v<-as.matrix(v)
> d<-matrix(nrow=nrow(v),ncol=nrow(x))
> for (i in 1:nrow(v)){
+ d[i,]<-sapply(1:nrow(x),function(z){dist(rbind(v[i,],x[z,]),method="manhattan")})
+ }
> print(d[1,1:10])
time taken for running the code is:
real 1m3.817s
user 1m3.543s
sys 0m0.031s
4) scenario4:
> x<-read.table("query.vec")
> v<-read.table("query.vec2")
> v<-as.matrix(v)
> d<-dist(rbind(v,x),method="manhattan")
> m<-as.matrix(d)
> m2<-m[1:nrow(v),(nrow(v)+1):nrow(x)]
> print(m2[1,1:10])
time taken for running the code:...