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The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate.

Produktbeschreibung
The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate.
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Autorenporträt
Shelly Gupta has done B.Tech. in IT from GJUS&T, India in 2009 & M.Tech. in CSE from Banasthali University, India in 2011. She has published 3 research papers at National /Intl level with 1 yr exp. in research. Her interests are in Data Mining & Software Engg. She is also a member of CSI (Computer Society of India). She is now working as lecturer.