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james_o_hagan
james_o_hagan
January 4, 2017
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Clustering in Data Workbench

  • January 4, 2017
  • 1 reply
  • 794 views

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

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Best answer by TanmayMathur

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.

1 reply

TanmayMathur
Adobe Employee
TanmayMathurAdobe EmployeeAccepted solution
Adobe Employee
January 19, 2017

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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