I am trying to calculate the distance between centroid and data points in KMean cluster using R.
Can anyone share with me the code for the same? Also it would be really helpful if you may provide the code for distance calculation between all data points in the cluster.
Hi Anmol
Using the built-in Iris data as an example, the following code does what you want:
kmeans_iris
Dear Anmol Banerjee ,
Clustering is a broad set of techniques for finding subgroups of observations within a data set. When we cluster observations, we want observations in the same group to be similar and observations in different groups to be dissimilar.
https://uc-r.github.io/kmeans_clustering
Regards,
Shafagat
I'll consider that I have 3 centroids & I'm trying to implement the computing of the distance between the centroids & the different data points, then I'll consider the min dist to assign the data point to a cluster.
#Calculate euclidean distance between centroid & data points, where column data[poisiton,1] represents the X and data[poisiton,2] represents the Y
#You can adapt the code based on the distance metric you're willing to consider; you can also add a loop on the centroid array in case you want to change the n_clusters .
dataerror = NA
datacluster = NA
for(position in 1:length(data$x)){
x
Check https://www.datasciencecentral.com/profiles/blogs/steps-to-calculate-centroids-in-cluster-using-k-means-clustering
Also check https://towardsdatascience.com/k-means-clustering-for-beginners-2dc7b2994a4
https://towardsdatascience.com/log-book-guide-to-distance-measuring-approaches-for-k-means-clustering-f137807e8e21
Also check this paper
http://infolab.stanford.edu/~ullman/mmds/ch7.pdf
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