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Classification is an important data mining task, and decision trees have emerged as a popular classifier due to their simplicity and relatively low computational complexity. Time required to build a decision tree becomes intractable, as datasets get extremely large. To overcome this problem we proposed a parallel mode of ID3 algorithm. Decision tree building is well-suited for thread-level parallelism...
Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is extremely important but complicated task that should be performed accurately and efficiently. This study analyzes the Behavioral Risk Factor Surveillance System, survey to test whether self-reported cardiovascular disease rates are higher in Singareni coal mining regions in Andhra Pradesh state,...
In this paper, we present a GA based methodology for extracting rules from radial basis function neural network trained by differential evolution. Rules are extracted using GATree. Here outputs predicted by the differential evolution trained radial basis function network along with the input variables are fed to the GATree for rule extraction purpose. The performance of the hybrid method was tested...
Tampering of documents is monotonically growing by posing challenges to forensic scientists. There is a great need to develop alternative solutions for forensic characterization of printers. This paper analyzes documents printed by various printers and characterizes them for identification purposes. Present study focuses on developing a model Gaussian variogram model (GVM) for identifying the print...
It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular. We have thus developed a unified and powerful approach termed MTdGRN (multiple time-delayed gene regulatory network) to discover the underlying gene regulations that can span any unit(s) of time intervals. A decision tree was used to extract the time-delayed...
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