Application of Data Mining in the Missing Information Guessing

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Provided by: International Publisher for Advanced Scientific Journals (IPASJ)
Topic: Data Management
Format: PDF
The classification downside is one in all the main problems in data processing as a result of it aims to extract a classifier which may be accustomed predict the classes of objects whose category table square measure unknown. In the case of classification with complete information, many algorithms are bestowed in literature. In the case of classification with incomplete information very few algorithms square measure there within the literature. The situation once data concerning the worth of some features is unknown isn't theoretical within the 1st case, the shortage of data is because of the impossibility of acting some tests once some data square measure missing some tests are often unessential when the classifier might check that selections without these check results.
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