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The Data Mining process encompasses many different specific techniques and algorithms that can be used to analyze the data and derive the discovered knowledge. An important problem regarding the results of the Data Mining process is the development of efficient indicators of assessing the quality of the results of the analysis. This, the quality assessment problem, is a cornerstone issue of the whole...
Summary The Data Mining process encompasses many different specific techniques and algorithms that can be used to analyze the data and derive the discovered knowledge. An important problem regarding the results of the Data Mining process is the development of efficient indicators of assessing the quality of the results of the analysis. This, the quality assessment problem, is a cornerstone issue of...
Although the goal of clustering is intuitively compelling and its notion arises in many fields, it is difficult to define a unified approach to address the clustering problem and thus diverse clustering algorithms abound in the research community. These algorithms, under different clustering assumptions, often lead to qualitatively different results. As a consequence the results of clustering algorithms...
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