Reference

---- (When published)

Code

The source code for DipTransformation is included here and can easily be imported into every Java-Editor und should be executable without any additional tweaking. One might have to add the path of the JdistLib-Library ("jdistlib-0.4.5-bin.jar"), which is alreaded included here.

The JdistLib-Library comes originally from here and is used for the Dip-Test.

Real-World Data and Results

The real-world data we used are in the directory "/dataset". The data sets are as follows:

• Whiteside
• Skinsegmentation
• Banknote Authentication
• Iris
• Prestige
• User Knowledge Modeling
• Mammographic Mass
• Seeds
• Breast Tissue
• Leaf

Additionale to that are also the DipTransformed data sets in the folder "/dataset". The transformed data set have an added "Dip" after the data set name, so is the transformed "Whiteside"-data set called "2 WhitesideDip".

The Running Example goes by the name of "tha". The DipTransformed version is called "thaDip".

Another metric: Adjusted Mutual Information

We used the NMI-score as a measure of comparison. We are aware of another frequently used, state-of-the-art metric for evaluating clustering results, called Adjusted Mutual Information (AMI). We have found that the results do not vary to the extent that the "take home message" changes, so we omit AMI results to reduce clutter.