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Data Mining: Practical Machine Learning Tools and Techniques
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This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.Abstract:
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. *Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects *Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods *Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualizationread more
Citations
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Journal ArticleDOI
A hybrid network intrusion detection system using simplified swarm optimization (SSO)
Yuk Ying Chung,Noorhaniza Wahid +1 more
TL;DR: A new hybrid intrusion detection system by using intelligent dynamic swarm based rough set (IDS-RS) for feature selection and simplified swarm optimization for intrusion data classification and a new weighted local search (WLS) strategy incorporated in SSO is proposed.
Journal ArticleDOI
Computational modeling and experimental validation of the Legionella and Coxiella virulence-related type-IVB secretion signal
Ziv Lifshitz,David Burstein,Michael Peeri,Tal Zusman,Kierstyn T. Schwartz,Howard A. Shuman,Tal Pupko,Gil Segal +7 more
TL;DR: This model is innovative because it enables searching ORFs for secretion signals on a genomic scale, which led to the identification and experimental validation of 20 effectors from Legionella pneumophila, Legionella longbeachae, and Coxiella burnetii and shows that this signal efficiently translocates into host cells in an Icm/Dot-dependent manner.
Proceedings ArticleDOI
Testing advanced driver assistance systems using multi-objective search and neural networks
TL;DR: This paper provides a testing approach for ADAS by combining multi-objective search with surrogate models developed based on neural networks, and shows that combining the search algorithm with surrogate modeling improves the quality of the generated test cases, especially under tight and realistic computational resources.
Proceedings ArticleDOI
A comprehensive investigation and comparison of Machine Learning Techniques in the domain of heart disease
Seyedamin Pouriyeh,Sara Vahid,Giovanna Sannino,Giuseppe De Pietro,Hamid R. Arabnia,Juan B. Gutierrez +5 more
TL;DR: Results of the experiments indicate that the SVM method using the boosting technique outperforms the other aforementioned methods for the prediction of heart disease.
Journal ArticleDOI
How valuable is medical social media data? Content analysis of the medical web
Kerstin Denecke,Wolfgang Nejdl +1 more
TL;DR: A method to classify blogs based on their information content is presented, which exploits high-level features describing the medical and affective content of blog posts, and shows that there are substantial differences in the content of various health-related Web resources.
References
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An introduction to the bootstrap
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A Coefficient of agreement for nominal Scales
TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.