By Oded Maimon, Lior Rokach

ISBN-10: 0387098224

ISBN-13: 9780387098227

This e-book organizes key techniques, theories, criteria, methodologies, traits, demanding situations and functions of knowledge mining and information discovery in databases. It first surveys, then offers entire but concise algorithmic descriptions of equipment, together with vintage tools plus the extensions and novel equipment built lately. It additionally provides in-depth descriptions of information mining purposes in quite a few interdisciplinary industries.

Show description

Read Online or Download Data Mining and Knowledge Discovery Handbook (Springer series in solid-state sciences) PDF

Similar data mining books

Fuzzy Sets in Management, Economy & Marketing by P.M. Pardalos PDF

The quick adjustments that experience taken position globally at the fiscal, social and company fronts characterised the 20 th century. The value of those adjustments has shaped an exceptionally advanced and unpredictable decision-making framework, that's tough to version via conventional techniques. the most function of this e-book is to provide the newest advances within the improvement of cutting edge ideas for dealing with the uncertainty that prevails within the international financial and administration environments.

Read e-book online JasperReports 3.5 for Java Developers PDF

This ebook is a entire and sensible consultant aimed toward getting the consequences you will have as quick as attainable. The chapters steadily increase your abilities and by means of the top of the publication you may be convinced adequate to layout robust stories. every one notion is obviously illustrated with diagrams and reveal photographs and easy-to-understand code.

Statistics, Data Mining, and Machine Learning in Astronomy: by Zeljko Ivezic, Andrew J. Connolly, Jacob T VanderPlas, PDF

Information, information Mining, and computing device studying in Astronomy: a realistic Python advisor for the research of Survey information (Princeton sequence in smooth Observational Astronomy)As telescopes, detectors, and pcs develop ever extra robust, the quantity of knowledge on the disposal of astronomers and astrophysicists will input the petabyte area, delivering actual measurements for billions of celestial items.

Download e-book for iPad: Data-Driven Process Discovery and Analysis: 4th by Paolo Ceravolo, Barbara Russo, Rafael Accorsi

This publication constitutes the completely refereed complaints of the Fourth foreign Symposium on Data-Driven strategy Discovery and research held in Riva del Milan, Italy, in November 2014. The 5 revised complete papers have been rigorously chosen from 21 submissions. Following the development, authors got the chance to enhance their papers with the insights they won from the symposium.

Extra resources for Data Mining and Knowledge Discovery Handbook (Springer series in solid-state sciences)

Example text

290-294. Levitin, A. & Redman, T. A Model of the Data (Life) Cycles with Application to Quality, Information and Software Technology 1995; 35(4):217-223. , Sung, S. , & Ling, T. W. A New Efficient Data cleansing Method. Proceedings of Database and Expert Systems Applications (DEXA 2002); 2002 September 2-6; Aix-en-Provence, France. 484-493. Maimon, O. and Rokach, L. Improving supervised learning by feature decomposition, Proceedings of the Second International Symposium on Foundations of Information and Knowledge Systems, Lecture Notes in Computer Science, Springer, 2002, 178-196 Maletic, J.

Space Decomposition In Data Mining: A Clustering Approach, Proceedings of the 14th International Symposium On Methodologies For Intelligent Systems, Maebashi, Japan, Lecture Notes in Computer Science, Springer-Verlag, 2003, pp. 24–31. Rokach, L. and Maimon, O. , Information Retrieval System for Medical Narrative Reports, Lecture Notes in Artificial intelligence 3055, page 217-228 SpringerVerlag, 2004. Rokach, L. and Maimon, O. , Selective voting-getting more for less in sensor fusion, International Journal of Pattern Recognition and Artificial Intelligence 20 (3) (2006), pp.

2, is created as a result of this method. 2. Dataset with Deleted Cases with Missing Attribute Values. 2. However, there are some reasons (Allison, 2002), (Little and Rubin, 2002) to consider it a good method. 2 The Most Common Value of an Attribute In this method, one of the simplest methods to handle missing attribute values, such values are replaced by the most common value of the attribute. In different words, a missing attribute value is replaced by the most probable known attribute value, where such probabilities are represented by relative frequencies of corresponding attribute values.

Download PDF sample

Data Mining and Knowledge Discovery Handbook (Springer series in solid-state sciences) by Oded Maimon, Lior Rokach

by Edward

New PDF release: Data Mining and Knowledge Discovery Handbook (Springer
Rated 4.28 of 5 – based on 9 votes