Classification of Melanomas in situ using Knowledge Discovery with Explained CBR

The goal of Knowledge Discovery is to extract knowledge from a set of data. Most common techniques used in knowledge discovery are based on clustering methods whose goal is to analyze a set of objects and to obtain clusters based on the similarity between these objects. A desirable characteristic of clustering results is that they should be easily understandable by domain experts. In this paper we introduce LazyCL, a procedure using a lazy learning method to produce explanations on clusters of unlabeled cases. These explanations are the basis on which experts can perform knowledge discovery. Here we use LazyCL to generate a domain theory for classification of melanomas in situ. Source URL: https://www.iiia.csic.es/en/node/53995 Links [1] https://www.iiia.csic.es/en/staff/eva-armengol [2] https://www.iiia.csic.es/en/bibliography?f[keyword]=806 [3] https://www.iiia.csic.es/en/bibliography?f[keyword]=433 [4] https://www.iiia.csic.es/en/bibliography?f[keyword]=661 [5] https://www.iiia.csic.es/en/bibliography?f[keyword]=507 [6] https://www.iiia.csic.es/en/bibliography?f[keyword]=442