*** TO CLARIFY ***
what i need is to modify the k-means algorithm so it calculates the optimal k for the algorithm - my criteria for finding the optimal k is by looking at inter cluster distances
i am using a k-means clustering algorithm to determine buckets of factors impacting a certain component. However, i am unable to modify the algorithm to help me get the optimal number of k clusters. i need help in modifying the algorithm to calculate the optimal number of cluster to use based on inter cluster distances. Challenge is that this has to be done in Excel using VBA. Attached is the K-means clustering algorithm to modify.
In addition, if above is doable, I would like it for the algorithm to go through the data and implement above for the different products i have without me having to separate the data by products and then running the algorithm.
Purpose is to identify most significant factors, if i run the algorithm against all factors per component would it help identify if any of them is insignificant or should i run it per factor to determine significant ones and then combine them?
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Hi Sir I have a lot of experience in Excel VBA and I have also used K means clustering so I understand what you require. I have programmed neural networks in vba before.