statistics - Dataset for density based clustering based on probability and possible cluster validation method -


Can anyone help me find a dataset to have property values ​​as points and class labels (cluster recognition Ground Truth) I want to find the possibility of every data item and use it for clustering.

Better Attribute Value User Score Score (1-bad, 2-satisfying, 3-good, 4-very good) for each attribute. I value property values ​​(like 1,2,3,4) Choice values ​​are preferred as it is easy to calculate the probability of each attribute value from these property values.

I got some dataets from the UCI repository but all the attribute values ​​did not get the score. Most (if not all) clustering algorithms are density-based.

There are a lot of survey literature on the clustering algorithm that you have to check. There are hundreds of literary density-based algorithms, including DBSCAN, Optis, Denkla ...

However, I have the assumption that you use the term "density-based" to be different from the literature. Do you refer to the possibility, not the density?

Do not expect clustering to label the class. Classes are not clusters Classes can be inseparable, or one class may include multiple clusters. The famous Iris data set, for example, intuitively consists of only 2 clusters (but 3 squares).

Evaluate and all this, check current questions and answers, please .

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