Cover Image

Data mining methods and models /

Provides an introduction into data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis.

Bibliographic Details
Main Author: Larose, Daniel T., (Author)
Format: eBook
Language:English
Published: Hoboken, NJ : Wiley-Interscience, [2006]
Subjects:
Data mining.
Exploration de données (Informatique)
COMPUTERS > Desktop Applications > Databases.
COMPUTERS > Database Management > General.
COMPUTERS > System Administration > Storage & Retrieval.
Electrical and Electronics Engineering
Electronic books.
Online Access:View fulltext via EzAccess
LEADER 05885cam a2200745Ii 4500
001 ocm85784185
003 OCoLC
005 20170124070632.8
006 m o d
007 cr cn|||||||||
008 070307t20062006njua ob 001 0 eng d
040 |a DG1  |b eng  |e rda  |e pn  |c DG1  |d BAKER  |d OKU  |d DG1  |d YDXCP  |d IEEEE  |d OCLCQ  |d DG1  |d GBVCP  |d OCLCQ  |d N$T  |d DST  |d TEFOD  |d EBLCP  |d E7B  |d MHW  |d NUKAT  |d REDDC  |d COO  |d DEBSZ  |d FTU  |d BTCTA  |d MERUC  |d IDEBK  |d INUAS  |d OCLCF  |d OCLCQ  |d MUX  |d UKWOH  |d NRU  |d UKDOC  |d OCLCQ  |d TEFOD  |d NNO  |d DEBBG 
016 7 |z 013301496  |2 Uk 
019 |a 64185846  |a 70160629  |a 70821819  |a 85820743  |a 156809570  |a 181837905  |a 209581249  |a 263593234  |a 441749408  |a 489550185  |a 647800679  |a 795324583 
020 |a 9780471756484  |q (electronic bk.) 
020 |a 0471756482  |q (electronic bk.) 
020 |a 9780471756477  |q (electronic bk.) 
020 |a 0471756474  |q (electronic bk.) 
020 |z 9780471666561  |q (print) 
020 |z 0471666564  |q (print) 
020 |a 9781118868676 
020 |a 1118868676 
024 7 |a 10.1002/0471756482  |2 doi 
029 1 |a AU@  |b 000041489242 
029 1 |a AU@  |b 000048760936 
029 1 |a AU@  |b 000051473107 
029 1 |a AU@  |b 000053281475 
029 1 |a DEBSZ  |b 377427241 
029 1 |a DEBSZ  |b 43031910X 
029 1 |a GBVCP  |b 091521181 
029 1 |a DEBBG  |b BV042988332 
029 1 |a NLGGC  |b 292177356 
029 1 |a DEBSZ  |b 475040678 
035 |a (OCoLC)85784185  |z (OCoLC)64185846  |z (OCoLC)70160629  |z (OCoLC)70821819  |z (OCoLC)85820743  |z (OCoLC)156809570  |z (OCoLC)181837905  |z (OCoLC)209581249  |z (OCoLC)263593234  |z (OCoLC)441749408  |z (OCoLC)489550185  |z (OCoLC)647800679  |z (OCoLC)795324583 
037 |a 110527837  |b Wiley InterScience  |n http://www3.interscience.wiley.com 
037 |a AD276CF7-3836-405A-9ACE-537E7EBE4A7D  |b OverDrive, Inc.  |n http://www.overdrive.com 
050 4 |a QA76.9.D343  |b L378 2006 
072 7 |a COM  |x 084010  |2 bisacsh 
072 7 |a COM  |x 021000  |2 bisacsh 
072 7 |a COM  |x 030000  |2 bisacsh 
082 0 4 |a 005.74  |2 22 
049 |a MAIN 
100 1 |a Larose, Daniel T.,  |e author  |4 aut 
245 1 0 |a Data mining methods and models /  |c Daniel T. Larose. 
264 1 |a Hoboken, NJ :  |b Wiley-Interscience,  |c [2006] 
264 4 |c ©2006 
300 |a 1 online resource (xvi, 322 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
505 0 0 |g 1.  |t DIMENSION REDUCTION METHODS.  |t Need for Dimension Reduction in Data Mining.  |t Principal Components Analysis.  |t Factor Analysis.  |t User-Defined Composites --  |g 2.  |t REGRESSION MODELING.  |t Example of Simple Linear Regression.  |t Least-Squares Estimates.  |t Coefficient of Determination.  |t Standard Error of the Estimate.  |t Correlation Coefficient.  |t ANOVA Table.  |t Outliers, High Leverage Points, and Influential Observations.  |t Regression Model.  |t Inference in Regression.  |t Verifying the Regression Assumptions.  |t Example: Baseball Data Set.  |t Example: California Data Set.  |t Transformations to Achieve Linearity --  |g 3.  |t MULTIPLE REGRESSION AND MODEL BUILDING.  |t Example of Multiple Regression.  |t Multiple Regression Model.  |t Inference in Multiple Regression.  |t Regression with Categorical Predictors.  |t Multicollinearity.  |t Variable Selection Methods.  |t Application of the Variable Selection Methods.  |t Mallows' Cp Statistic.  |t Variable Selection Criteria.  |t Using the Principal Components as Predictors --  |g 4.  |t LOGISTIC REGRESSION.  |t Simple Example of Logistic Regression.  |t Maximum Likelihood Estimation.  |t Interpreting Logistic Regression Output.  |t Inference: Are the Predictors Significant?.  |t Interpreting a Logistic Regression Model.  |t Assumption of Linearity.  |t Zero-Cell Problem.  |t Multiple Logistic Regression.  |t Introducing Higher-Order Terms to Handle Nonlinearity.  |t Validating the Logistic Regression Model.  |t WEKA: Hands-on Analysis Using Logistic Regression --  |g 5.  |t NAIVE BAYES ESTIMATION AND BAYESIAN NETWORKS.  |t Bayesian Approach.  |t Maximum a Posteriori Classification.  |t Naïve Bayes Classification.  |t WEKA: Hands-on Analysis Using Naive Bayes.  |t Bayesian Belief Networks.  |t WEKA: Hands-On Analysis Using the Bayes Net Classifier --  |g 6.  |t GENETIC ALGORITHMS.  |t Introduction to Genetic Algorithms.  |t Basic Framework of a Genetic Algorithm.  |t Simple Example of a Genetic Algorithm at Work.  |t Modifications and Enhancements: Selection.  |t Modifications and Enhancements: Crossover.  |t Genetic Algorithms for Real-Valued Variables.  |t Using Genetic Algorithms to Train a Neural Network.  |t WEKA: Hands-on Analysis Using Genetic Algorithms --  |g 7.  |t CASE STUDY: MODELING RESPONSE TO DIRECT MAIL MARKETING.  |t Cross-Industry Standard Process for Data Mining.  |t Business Understanding Phase.  |t Data Understanding and Data Preparation Phases.  |t Modeling and Evaluation Phases. 
520 |a Provides an introduction into data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis. 
588 0 |a Print version record and online resource; title from PDF title page (IEEE Xplore, viewed March 14, 2014). 
650 0 |a Data mining. 
650 6 |a Exploration de données (Informatique) 
650 7 |a COMPUTERS  |x Desktop Applications  |x Databases.  |2 bisacsh 
650 7 |a COMPUTERS  |x Database Management  |x General.  |2 bisacsh 
650 7 |a COMPUTERS  |x System Administration  |x Storage & Retrieval.  |2 bisacsh 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
653 |a Electrical and Electronics Engineering 
655 4 |a Electronic books. 
776 0 8 |i Print version:  |a Larose, Daniel T.  |t Data mining methods and models.  |d Hoboken, NJ : Wiley-Interscience, ©2006  |z 0471666564  |z 9780471666561  |w (DLC) 2005010801  |w (OCoLC)59223748 
856 4 0 |z View fulltext via EzAccess  |u https://ezaccess.library.uitm.edu.my/login?url=https://doi.org/10.1002/0471756482 
994 |a 92  |b DG1 

Similar Items