Oops. > (ii) Your distance calculation is not the cartesian distance. That would be: > sqrt(rowSums(iris2[1,]^2 - centers[1,]^2)). Strike that. Need more coffee :-O
> On 2014-05-07, at 4:34 AM, marioger wrote: > >> Hi, >> >> i am hoping you can help me with my problem. I am trying to detect outliers >> with use of the kmeans algorithm. First I perform the algorithm and choose >> those object as possible outliers which have a big distance to their cluster >> center. Instead of using the absolute distance I want to use the relative >> distance, i.e. the ration of absolute distance of the object to the cluster >> center and the average distance of all objects of the cluster to their >> cluster center. The code for outlier detection based on absolute distance is >> the following: >> >>> # remove species from the data to cluster >>> iris2 <- iris[,1:4] >>> kmeans.result <- kmeans(iris2, centers=3) >>> # cluster centers >>> kmeans.result$centers >>> # calculate distances between objects and cluster centers >>> centers <- kmeans.result$centers[kmeans.result$cluster, ] >>> distances <- sqrt(rowSums((iris2 - centers)^2)) >>> # pick top 5 largest distances >>> outliers <- order(distances, decreasing=T)[1:5] >>> # who are outliers >>> print(outliers) >> >> But how can I use the relative instead of the absolute distance to find >> outliers? >> Thanks in advance. >> >> Mario >> >> >> >> -- >> View this message in context: >> http://r.789695.n4.nabble.com/Outlier-Detection-with-k-Means-tp4690098.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
