Hi all,
The company I work at is getting Data Workbench and I was reading up on the clustering options in the predictive analytics section and had a few questions on it.
1. The clustering option uses k-means to partition your data set correct? So why isn't this considered a descriptive analytics option ? Is there some feature that makes predictions for each of these clusters that's not in the documentation
2. A critical part of k-means clustering is normalization what type of normalization goes on when someone uses this product?
Full disclosure I haven't actually used the product yet so I'm sure there are a lot of features that I haven't looked at yet that might warrant grouping in the clustering tool with the other predictive analytics tools.
Best,
James O'Hagan