default search action
The Data Mining and Knowledge Discovery Handbook 2005
- Oded Maimon, Lior Rokach:
The Data Mining and Knowledge Discovery Handbook. Springer 2005, ISBN 0-387-24435-2 - Oded Maimon, Lior Rokach:
Introduction to Knowledge Discovery in Databases. The Data Mining and Knowledge Discovery Handbook 2005: 1-17
Part I: Preprocessing Methods
- Jonathan I. Maletic, Andrian Marcus:
Data Cleansing - A Prelude to Knowledge Discovery. The Data Mining and Knowledge Discovery Handbook 2005: 21-36 - Jerzy W. Grzymala-Busse, Witold J. Grzymala-Busse:
Handling Missing Attribute Values. The Data Mining and Knowledge Discovery Handbook 2005: 37-57 - Christopher J. C. Burges:
Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour. The Data Mining and Knowledge Discovery Handbook 2005: 59-92 - Barak Chizi, Oded Maimon:
Dimension Reduction and Feature Selection. The Data Mining and Knowledge Discovery Handbook 2005: 93-111 - Ying Yang, Geoffrey I. Webb, Xindong Wu:
Discretization Methods. The Data Mining and Knowledge Discovery Handbook 2005: 113-130 - Irad E. Ben-Gal:
Outlier Detection. The Data Mining and Knowledge Discovery Handbook 2005: 131-146
Part II: Supervised Methods
- Oded Maimon, Lior Rokach:
Introduction to Supervised Methods. The Data Mining and Knowledge Discovery Handbook 2005: 149-164 - Lior Rokach, Oded Maimon:
Decision Trees. The Data Mining and Knowledge Discovery Handbook 2005: 165-192 - Paola Sebastiani, María M. Abad-Grau, Marco Ramoni:
Bayesian Networks. The Data Mining and Knowledge Discovery Handbook 2005: 193-230 - Richard A. Berk:
Data Mining within a Regression Framework. The Data Mining and Knowledge Discovery Handbook 2005: 231-255 - Armin Shmilovici:
Support Vector Machines. The Data Mining and Knowledge Discovery Handbook 2005: 257-276 - Jerzy W. Grzymala-Busse:
Rule Induction. The Data Mining and Knowledge Discovery Handbook 2005: 277-294
Part III: Unsupervised Methods
- Alfred Inselberg:
Visualization and Data Mining for High Dimensional Datasets. The Data Mining and Knowledge Discovery Handbook 2005: 297-319 - Lior Rokach, Oded Maimon:
Clustering Methods. The Data Mining and Knowledge Discovery Handbook 2005: 321-352 - Frank Höppner:
Association Rules. The Data Mining and Knowledge Discovery Handbook 2005: 353-376 - Bart Goethals:
Frequent Set Mining. The Data Mining and Knowledge Discovery Handbook 2005: 377-397 - Jean-François Boulicaut, Baptiste Jeudy:
Constraint-Based Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 399-416 - Steve Donoho:
Link Analysis. The Data Mining and Knowledge Discovery Handbook 2005: 417-432
Part IV: Soft Computing Methods
- Alex Alves Freitas:
Evolutionary Algorithms for Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 435-467 - Shahar Cohen, Oded Maimon:
Reinforcement-Learning: An Overview from a Data Mining Perspective. The Data Mining and Knowledge Discovery Handbook 2005: 469-486 - G. Peter Zhang:
Neural Networks. The Data Mining and Knowledge Discovery Handbook 2005: 487-516 - Joseph Komem, Moti Schneider:
On the Use of Fuzzy Logic in Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 517-533 - Tsau Young Lin, Churn-Jung Liau:
Granular Computing and Rough Sets. The Data Mining and Knowledge Discovery Handbook 2005: 535-561
Part V: Supporting Methods
- Yoav Benjamini, Moshe Leshno:
Statistical Methods for Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 565-587 - Petr Hájek:
Logics for Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 589-602 - Tao Li, Sheng Ma, Mitsunori Ogihara:
Wavelet Methods in Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 603-626 - Daniel Barbará, Ping Chen:
Fractal Mining - Self Similarity-based Clustering and its Applications. The Data Mining and Knowledge Discovery Handbook 2005: 627-647 - Sigal Sahar:
Interestingness Measures - On Determining What Is Interesting. The Data Mining and Knowledge Discovery Handbook 2005: 649-660 - Maria Halkidi, Michalis Vazirgiannis:
Quality Assessment Approaches in Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 661-696 - Paolo Giudici:
Data Mining Model Comparison. The Data Mining and Knowledge Discovery Handbook 2005: 697-714 - Jean-François Boulicaut, Cyrille Masson:
Data Mining Query Languages. The Data Mining and Knowledge Discovery Handbook 2005: 715-727
Part VI: Advanced Methods
- Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil:
Meta-Learning. The Data Mining and Knowledge Discovery Handbook 2005: 731-748 - Pierre Geurts:
Bias vs. Variance Decomposition for Regression and Classification. The Data Mining and Knowledge Discovery Handbook 2005: 749-763 - Gary M. Weiss:
Mining with Rare Cases. The Data Mining and Knowledge Discovery Handbook 2005: 765-776 - Haixun Wang, Philip S. Yu, Jiawei Han:
Mining Data Streams. The Data Mining and Knowledge Discovery Handbook 2005: 777-792 - Wei Wang, Jiong Yang:
Mining High-Dimensional Data. The Data Mining and Knowledge Discovery Handbook 2005: 793-799 - Moty Ben-Dov, Ronen Feldman:
Text Mining and Information Extraction. The Data Mining and Knowledge Discovery Handbook 2005: 801-831 - Shashi Shekhar, Pusheng Zhang, Yan Huang:
Spatial Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 833-851 - Nitesh V. Chawla:
Data Mining for Imbalanced Datasets: An Overview. The Data Mining and Knowledge Discovery Handbook 2005: 853-867 - Saso Dzeroski:
Relational Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 869-898 - Johannes Fürnkranz:
Web Mining. The Data Mining and Knowledge Discovery Handbook 2005: 899-920 - Nora Oikonomakou, Michalis Vazirgiannis:
A Review of Web Document Clustering Approaches. The Data Mining and Knowledge Discovery Handbook 2005: 921-943 - Hong Yao, Cory J. Butz, Howard J. Hamilton:
Causal Discovery. The Data Mining and Knowledge Discovery Handbook 2005: 945-955 - Lior Rokach:
Ensemble Methods for Classifiers. The Data Mining and Knowledge Discovery Handbook 2005: 957-980 - Oded Maimon, Lior Rokach:
Decomposition Methodology for Knowledge Discovery and Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 981-1003 - Vicenç Torra:
Information Fusion - Methods and Aggregation Operators. The Data Mining and Knowledge Discovery Handbook 2005: 1005-1016 - Antonio Congiusta, Domenico Talia, Paolo Trunfio:
Parallel and Grid-Based Data Mining - Algorithms, Models and Systems for High-Performance KDD. The Data Mining and Knowledge Discovery Handbook 2005: 1017-1041 - Steve Moyle:
Collaborative Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 1043-1056 - Hamid R. Nemati, Christopher D. Barko:
Organizational Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 1057-1067 - Chotirat (Ann) Ratanamahatana, Jessica Lin, Dimitrios Gunopulos, Eamonn J. Keogh, Michail Vlachos, Gautam Das:
Mining Time Series Data. The Data Mining and Knowledge Discovery Handbook 2005: 1069-1103
Part VII: Applications
- Nada Lavrac, Blaz Zupan:
Data Mining in Medicine. The Data Mining and Knowledge Discovery Handbook 2005: 1107-1138 - Gautam B. Singh:
Learning Information Patterns in Biological Databases. The Data Mining and Knowledge Discovery Handbook 2005: 1139-1158 - Bruno Agard, Andrew Kusiak:
Data Mining for Selection of Manufacturing Processes. The Data Mining and Knowledge Discovery Handbook 2005: 1159-1166 - Yoram Reich:
Data Mining of Design Products and Processes. The Data Mining and Knowledge Discovery Handbook 2005: 1167-1187 - Gary M. Weiss:
Data Mining in Telecommunications. The Data Mining and Knowledge Discovery Handbook 2005: 1189-1201 - Boris Kovalerchuk, Evgenii Vityaev:
Data Mining for Financial Applications. The Data Mining and Knowledge Discovery Handbook 2005: 1203-1224 - Anoop Singhal, Sushil Jajodia:
Data Mining for Intrusion Detection. The Data Mining and Knowledge Discovery Handbook 2005: 1225-1237 - Mark Last:
Data Mining for Software Testing. The Data Mining and Knowledge Discovery Handbook 2005: 1239-1248 - Kurt H. Thearling:
Data Mining for CRM. The Data Mining and Knowledge Discovery Handbook 2005: 1249-1259 - Nissan Levin, Jacob Zahavi:
Data Mining for Target Marketing. The Data Mining and Knowledge Discovery Handbook 2005: 1261-1301
Part VIII: Software
- Eibe Frank, Mark A. Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer:
WEKA - A Machine Learning Workbench for Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 1305-1314 - Pablo Tamayo, Charles Berger, Marcos M. Campos, Joseph Yarmus, Boriana L. Milenova, Ari Mozes, Margaret Taft, Mark F. Hornick, Ramkumar Krishnan, Shiby Thomas, Mark Kelly, Denis Mukhin, Robert Haberstroh, Susie Stephens, Jacek Myczkowsji:
Oracle Data Mining - Data Mining in the Database Environment. The Data Mining and Knowledge Discovery Handbook 2005: 1315-1329 - ZhaoHui Tang, Jamie Maclennan, Pyungchul (Peter) Kim:
Building Data Mining Solutions with OLE DB for DM and XML for Analysis. The Data Mining and Knowledge Discovery Handbook 2005: 1331-1345 - Jerzy W. Grzymala-Busse:
LERS - A Data Mining System. The Data Mining and Knowledge Discovery Handbook 2005: 1347-1351 - Nissan Levin, Jacob Zahavi:
GainSmarts Data Mining System for Marketing. The Data Mining and Knowledge Discovery Handbook 2005: 1353-1364 - Abraham Meidan:
Wizsoft's WizWhy. The Data Mining and Knowledge Discovery Handbook 2005: 1365-1369 - Joseph Komem, Moti Schneider:
DataEngine - Tools for Intelligent Data Analysis and Control. The Data Mining and Knowledge Discovery Handbook 2005: 1371-1377
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.