Intrusion Detection Methods Using an Ensemble of Decision Trees
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2017, 2017
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 48.81
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Add to basketItem description from seller
This item is printed on demand - it takes 3-4 days longer - Neuware -Intrusion detection corresponds to a set of techniques that are used to find attacks which damages the computers and network infrastructures. Intrusion detection is a classification problem. Therefore, data mining techniques can be used to classify a given network connection to either a normal connection or an anomaly connection. To do this, various classification models can be used. Among all, decision tree classifiers have become very popular because of its simplicity, interpretability and its performance. However, decision tree classifiers are known to have high variance. Therefore, it is said to be an unstable classifier. Along with these, the conventional decision tree classifier does not perform well when noise, vagueness and uncertainty present in the data. However, to resolve the above issues this book proposes to use an ensemble of decision tree classifiers. To show the effectiveness of the proposed methods, various intrusion detection data sets along with standard data sets are used. 140 pp. Englisch. …
Seller Inventory # 9786202008396
- Title
- Intrusion Detection Methods Using an Ensemble of Decision Trees
- Author
- Gulla Kishor Kumar
- Publisher
- LAP LAMBERT Academic Publishing Jul 2017
- Publication year
- 2017
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 6202008393
- ISBN 13
- 9786202008396
- Item weight
- 227 grams
- Dimensions
- 220x150x9 mm
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About the Author
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BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
Shipping rates from Germany to U.S.A.
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