Achieving application requirements
Distributed systems
Bioinformatics—an introduction for computer scientists
ACM Computing Surveys (CSUR)
ACM SIGKDD Explorations Newsletter
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning (Studies in Computational Intelligence)
Associative memory approach for the diagnosis of parkinson's disease
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
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In this paper we have discussed the importance of data mining in the field of bioinformatics and various subfields of bioinformatics in which data mining has shown its great impact. Using a data mining tool, Weka, we pre- process the dataset on which we have worked and then using one of the classification methods i.e. Support Vector Machine method (SVM), we distinguished people with Parkinson's disease from the healthy people. Appling libsvm we have tried to find the best possible accuracy on different kernel values for the given dataset. We study the ROC curve variation, and the way the value of true positive and false positive rates changes with increasing number of the cross validation folds.