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Knowledge Discovery About Cancer Based on Fuzzy Pbkp_redicates

Abstract:

Knowledge discovery information was analyzed in references regarding the health area. The problem is the lack of a generalized classification of cancer-based on fuzzy pbkp_redicates, the challenge is the extraction of information from a data set. The objective is to perform a fuzzy pbkp_redicate based on cancer knowledge discovery analysis to find time optimization of data and results. Empirical - analytical research with a quantitative approach was applied, its method is quasi-experimental and the technique of sampling a specific group of references was used. The application of materials resulted in an Analysis of the relationship between variables, a correlation between Monoplot, and Similarities between observations. It was concluded that the discovery of knowledge generates new quantitative information on the correlations between the attributes belonging to a data set; We use Principal Component Analysis which is a knowledge-based model to analyze positive or negative correlations between attributes or variables.