Titlebook: Data Preprocessing in Data Mining; Salvador García,Julián Luengo,Francisco Herrera Book 2015 Springer International Publishing Switzerland

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Dealing with Noisy Data,nces in classification problems. Noise is an unavoidable problem, which affects the data collection and data preparation processes in Data Mining applications, where errors commonly occur. The performance of the models built under such circumstances will heavily depend on the quality of the training

屈尊

Data Reduction, and attributes; and simplifying the domain of the data. A global overview to this respect is given in Sect. .. One of the well-known problems in Data Mining is the “curse of dimensionality”, related with the usual high amount of attributes in data. Section . deals with this problem. Data sampling a

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Instance Selection,t of all, we define a broader perspective on concepts and topics related with instance selection (Sect. .). Due to the fact that instance selection has been distinguished over the years as two type of tasks, depending on the data mining method applied later, we clearly separate it into two processes

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Communications Standard Dictionary. An overview of discretization together with a complete outlook and taxonomy are supplied in Sects. . and .. We conduct an experimental study in supervised classification involving the most representative discretizers, different types of classifiers, and a large number of data sets (Sect. .).