prediction accuracy for clustering

Hi everyone,
I wondering how I can get "prediction accuracy" for different clustering techniques in RapidMiner? Because the default performance measures such as "cluster distance performance" or "cluster density performance" do not provide prediction accuracy.
Thanks in advance,
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For example, in my dataset I have 11 normal attributes and 1 lable. In classification, we get prediction accuracy based on the confusion matrix. For clustering, there is no such thing but I need a prediction performance as many papers comparing their clustering algorithms based on this measure. Fo instance, the attached image shows one of these papers which provides predicttion performance for expectation maximization and k-means.
Thaks
hello @vand_boo99 welcome to the community! I'd recommend posting your XML process here (see https://youtu.be/KkgB5QXWXJ8 and "Read Before Posting" on right when you reply) and attach your dataset. This way we can replicate what you're doing and help you better.
Scott
Hi,
how do you define accuracy if there is no label like in usual clustering problems?
~Martin