PERCEPTION OF TIRED BLOOD AND ITS CAUSES USING MINING TECHNIQUESJournal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.4, No. 1)
Publication Date: 2015-01-30
Authors : N.Tamil Selvi; S.Saranya; P.Usha; M.yasodha;
Page : 505-508
Keywords : Machine learning algorithm; CHC; CBC; Anemia; Tired Blood; WEKA.;
The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as ‘data mining’ offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. Recent progress in data mining research has led to the developments of numerous efficient and scalable methods for mining interesting patterns and knowledge in large databases, ranging from efficient classification methods to clustering, outlier analysis, frequent, sequential and structured pattern analysis methods, and visualization and spatial/temporal data analysis tools.
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Last modified: 2015-02-09 22:26:07