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
Solved! Go to Solution.
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Hi James,
1. The clustering feature is part of the predictive workflow made available with Analytics Premium. To your point, it is a descriptive component of that workflow.
2. Users can choose between two normalization methods. Either the Min-Max or the Z-Score technique. The Min-Max method is enabled by default.
I hope that helps.
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Hi James,
1. The clustering feature is part of the predictive workflow made available with Analytics Premium. To your point, it is a descriptive component of that workflow.
2. Users can choose between two normalization methods. Either the Min-Max or the Z-Score technique. The Min-Max method is enabled by default.
I hope that helps.
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Total Likes