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Outlier Detection, Clustering, and Classification -Methodologically Unified Procedures for Conditional Approach

机译:异常值检测,聚类和分类 - 统一方法的条件方法

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The subject of the study are three fundamental procedures of contemporary data analysis: outliers detection, clustering and classification. The issue is considered in a conditional approach - introduction of specific (e.g. current) values to the model allows in practice a significantly precise description of the reality under research. The same methodology has been used for all three above tasks, which considerably facilitates the interpretations, potential modifications and practical applications of the material investigated. Using non-parametric methods frees the procedures under investigation from a distribution in the considered dataset.
机译:该研究的主题是当代数据分析的三个基本程序:异常值检测,聚类和分类。 该问题是以条件的方法考虑 - 将特定(例如当前)值引入模型中的实践在实践中明显精确描述了研究的现实。 对于所有三个以上任务使用相同的方法,这大大促进了所研究的材料的解释,潜在的修改和实际应用。 使用非参数方法将在考虑数据集的分发中释放调查的过程。

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