Classification of data mining techniques in intrusion detection
Language: English
Published by LAP LAMBERT Academic Publishing Aug 2013, 2013
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 31.71
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Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -Data mining is the process of gathering, searching, and analyzing a large amount of raw data, as to discover patterns, relationships and behavior of data. There are large numbers of algorithms for classification of data mining. Single algorithm is not efficient for classification of data and recognize their pattern and behavior .There is a key term known as ensemble learning which means Combining two or more classifiers for efficient result. I have used the KDD'99 dataset for the experiment which have 41 features labeled either as normal or as an attack. In this book I have represented how graphical machine learning tool weka can be used for data mining and how ensemble learning can be implemented using weka.I have used three classifiers with the Bagging and Boosting ensemble learning approach which are complementary naïve bayes and two are rule based classifiers, part and jrip. My experiment shows that bagging improves the efficiency of the rule based classifiers as well as of naïve Bayes. However, the rule based classifiers become more efficient with bagging and boosting techniques.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…
Seller Inventory # 9783659442155
- Title
- Classification of data mining techniques in intrusion detection
- Author
- Gaurav Mishra
- Publisher
- LAP LAMBERT Academic Publishing Aug 2013
- Publication year
- 2013
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3659442151
- ISBN 13
- 9783659442155
- Item weight
- 96 grams
- Dimensions
- 220x150x4 mm
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buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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