Stuck with an error implementing kmeans in r

[jenithareddy]

I am trying to implement kmeans clustering algorithm using Manhattan distance. I used the following code for implementing the same:

data<- read.csv("garments_worker_productivity.csv")
cluster<-kmeans(data,3,iter.max=10, nstart=1, method = "Manhattan")

I am receiving the following error:

Error in kmeans(data, 3, iter.max = 10, nstart = 1, method = "manhattan") : 
  unused argument (method = "Manhattan")

so how do I implement kmeans using Manhattan and Minkowski distance in r without an error?

thank you!

[FJCC]

The kmeans function in the stats package has an argument named algorithm. None of the values it can have is "manhattan".

kmeans(x, centers, iter.max = 10, nstart = 1,
       algorithm = c("Hartigan-Wong", "Lloyd", "Forgy",
                     "MacQueen"), trace=FALSE)

Is that the function you are using?

[jenithareddy]

yes. I realised I was trying this function in amap package

Kmeans(x, centers, iter.max = 10, nstart = 1,
         method = "euclidean")

Is there any other way where I can use Manhattan or Minkowski distance instead of the traditional Euclidean distance in the Kmeans algorithm? Please do let me know how.
Thank you!

[FJCC]

Kmeans() accepts the following values of method:

"euclidean", "maximum",
"manhattan", "canberra", "binary", "pearson" , "abspearson" , "abscorrelation",
"correlation", "spearman" or "kendall"

Notice "manhattan" is all lower case.

[jenithareddy]

Still it shows the same error

[FJCC]

kmeans is the function from the stats package. Kmeans, with an uppercase K, is the function from amap. Case matters in R.

[jenithareddy]

it says that the function isn't found ;(

[FJCC]

Did you run

library(amap)

before trying to use Kmeans()? That assumes you have installed the amap package.

[jenithareddy]

yes I did. amap package is installed

[jenithareddy]

I removed the line

library(amap)

and it worked.. I still don't know why.. thanks though!