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Data Mining: Practical Machine Learning Tools and Techniques
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TLDR
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
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The Act of Creation
TL;DR: Koestler as mentioned in this paper examines the idea that we are at our most creative when rational thought is suspended, for example, in dreams and trancelike states, and concludes that "the act of creation is the most creative act in human history".
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CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine
TL;DR: A support vector machine-based classifier, named Coding Potential Calculator (CPC), to assess the protein-coding potential of a transcript based on six biologically meaningful sequence features, which can discriminate coding from noncoding transcripts with high accuracy.
Proceedings Article
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
Jesús Alcalá-Fdez,Alberto Fernández,Julián Luengo,Joaquín Derrac,Salvador García,Luciano Sánchez,Francisco Herrera +6 more
TL;DR: The aim of this paper is to present three new aspects of KEEL: KEEL-dataset, a data set repository which includes the data set partitions in theKEELformat and some guidelines for including new algorithms in KEEL, helping the researcher to compare the results of many approaches already included within the KEEL software.
Journal ArticleDOI
Classifier chains for multi-label classification
TL;DR: This paper presents a novel classifier chains method that can model label correlations while maintaining acceptable computational complexity, and illustrates the competitiveness of the chaining method against related and state-of-the-art methods, both in terms of predictive performance and time complexity.
Journal ArticleDOI
Machine learning applications in cancer prognosis and prediction.
Konstantina Kourou,Themis P. Exarchos,Konstantinos P. Exarchos,Michalis V. Karamouzis,Dimitrios I. Fotiadis +4 more
TL;DR: Given the growing trend on the application of ML methods in cancer research, this work presents here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.
References
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