THE USAGE OF MARGIN-BASED FEATURE SELECTION ALGORITHM IN IVF ICSI/ET DATA ANALYSIS
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In the case of infertility treatment, successful classification will facilitate understanding of various factors affecting the success of the process. Classification itself is an important data mining problem. Many classifications and constructions of the classifier algorithms are not able to cope with the analysis of the huge amount of factors associated with this process. Feature selection allows to significantly reduce the volume of analyzed data, while maintaining the classifier prediction quality. This leads to the rejection of nonessential measurements and time reductions.
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