Performance Analysis of Data Mining Classification Techniques : Performance Analysis of Various Data Mining Classification Techniques on Healthcare Data

Shelly Gupta

ISBN 10: 3848438755 / ISBN 13: 9783848438754

Editore: LAP LAMBERT Academic Publishing, 2012

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nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Codice articolo 9783848438754

Dati bibliografici

• Titolo: Performance Analysis of Data Mining Classification Techniques : Performance Analysis of Various Data Mining Classification Techniques on Healthcare Data
• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 3848438755
• ISBN 13: 9783848438754
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 5 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 5 millimetri di profondità
• Peso: 131 grammi

Descrizione articolo

Riassunto

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.

L'autore

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.