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ORCIDData Mining and Knowledge Discovery Handbook 2010
- Oded Maimon, Lior Rokach:
Data Mining and Knowledge Discovery Handbook, 2nd ed. Springer 2010, ISBN 978-0-387-09822-7
Part 1 / Preprocessing Methods
- Oded Maimon, Lior Rokach:
Introduction to Knowledge Discovery and Data Mining. 1-15 - Jonathan I. Maletic, Andrian Marcus:
Data Cleansing: A Prelude to Knowledge Discovery. 19-32 - Jerzy W. Grzymala-Busse, Witold J. Grzymala-Busse:
Handling Missing Attribute Values. 33-51 - Christopher J. C. Burges:
Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour. 53-82 - Barak Chizi, Oded Maimon:
Dimension Reduction and Feature Selection. 83-100 - Ying Yang, Geoffrey I. Webb
, Xindong Wu:
Discretization Methods. 101-116 - Irad Ben-Gal:
Outlier Detection. 117-130
Part 2 / Supervised Methods
- Lior Rokach, Oded Maimon:
Supervised Learning. 133-147 - Lior Rokach, Oded Maimon:
Classification Trees. 149-174 - Paola Sebastiani, María M. Abad-Grau, Marco Ramoni:
Bayesian Networks. 175-208 - Richard A. Berk:
Data Mining within a Regression Framework. 209-230 - Armin Shmilovici:
Support Vector Machines. 231-247 - Jerzy W. Grzymala-Busse:
Rule Induction. 249-265
Part 3 / Unsupervised Methods
- Lior Rokach:
A survey of Clustering Algorithms. 269-298 - Frank Höppner:
Association Rules. 299-319 - Bart Goethals:
Frequent Set Mining. 321-338 - Jean-François Boulicaut, Baptiste Jeudy:
Constraint-based Data Mining. 339-354 - Steve Donoho:
Link Analysis. 355-368
Part 4 / Soft Computing Methods
- Alex Alves Freitas:
A Review of Evolutionary Algorithms for Data Mining. 371-400 - Oded Maimon, Shahar Cohen:
A Review of Reinforcement Learning Methods. 401-417 - G. Peter Zhang:
Neural Networks For Data Mining. 419-444 - Tsau Young Lin, Churn-Jung Liau:
Granular Computing and Rough Sets - An Incremental Development. 445-468 - Swagatam Das, Ajith Abraham:
Pattern Clustering Using a Swarm Intelligence Approach. 469-504 - Lior Rokach:
Using Fuzzy Logic in Data Mining. 505-520
Part 5 / Supporting Methods
- Yoav Benjamini, Moshe Leshno:
Statistical Methods for Data Mining. 523-540 - Petr Hájek:
Logics for Data Mining. 541-551 - Tao Li, Sheng Ma, Mitsunori Ogihara:
Wavelet Methods in Data Mining. 553-571 - Daniel Barbará, Ping Chen:
Fractal Mining - Self Similarity-based Clustering and its Applications. 573-589 - Noa Ruschin Rimini, Oded Maimon:
Visual Analysis of Sequences Using Fractal Geometry. 591-601 - Sigal Sahar:
Interestingness Measures - On Determining What Is Interesting. 603-612 - Maria Halkidi, Michalis Vazirgiannis:
Quality Assessment Approaches in Data Mining. 613-639 - Paolo Giudici:
Data Mining Model Comparison. 641-654 - Jean-François Boulicaut, Cyrille Masson:
Data Mining Query Languages. 655-664
Part 6 / Advanced Methods
- Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Mining Multi-label Data. 667-685 - Vicenç Torra:
Privacy in Data Mining. 687-716 - Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil:
Meta-Learning - Concepts and Techniques. 717-731 - Pierre Geurts:
Bias vs Variance Decomposition for Regression and Classification. 733-746 - Gary M. Weiss:
Mining with Rare Cases. 747-757 - Mohamed Medhat Gaber, Arkady B. Zaslavsky, Shonali Krishnaswamy:
Data Stream Mining. 759-787 - Haixun Wang, Philip S. Yu, Jiawei Han:
Mining Concept-Drifting Data Streams. 789-802 - Wei Wang, Jiong Yang:
Mining High-Dimensional Data. 803-808 - Moty Ben-Dov, Ronen Feldman:
Text Mining and Information Extraction. 809-835 - Shashi Shekhar, Pusheng Zhang, Yan Huang:
Spatial Data Mining. 837-854 - Slava Kisilevich, Florian Mansmann, Mirco Nanni, Salvatore Rinzivillo:
Spatio-temporal clustering. 855-874 - Nitesh V. Chawla:
Data Mining for Imbalanced Datasets: An Overview. 875-886 - Saso Dzeroski:
Relational Data Mining. 887-911 - Johannes Fürnkranz:
Web Mining. 913-929 - Nora Oikonomakou, Michalis Vazirgiannis:
A Review of Web Document Clustering Approaches. 931-948 - Hong Yao, Cory J. Butz, Howard J. Hamilton:
Causal Discovery. 949-958 - Lior Rokach:
Ensemble Methods in Supervised Learning. 959-979 - Lior Rokach, Oded Maimon:
Data Mining using Decomposition Methods. 981-998 - Vicenç Torra:
Information Fusion - Methods and Aggregation Operators. 999-1008 - Antonio Congiusta, Domenico Talia, Paolo Trunfio:
Parallel and Grid-Based Data Mining - Algorithms, Models and Systems for High-Performance KDD. 1009-1028 - Steve Moyle:
Collaborative Data Mining. 1029-1039 - Hamid R. Nemati, Christopher D. Barko:
Organizational Data Mining. 1041-1048 - Chotirat Ann Ratanamahatana, Jessica Lin, Dimitrios Gunopulos, Eamonn J. Keogh, Michail Vlachos, Gautam Das:
Mining Time Series Data. 1049-1077
Part 7 / Applications
- Zhongfei (Mark) Zhang, Ruofei Zhang:
Multimedia Data Mining. 1081-1109 - Nada Lavrac, Blaz Zupan:
Data Mining in Medicine. 1111-1136 - Gautam B. Singh:
Learning Information Patterns in Biological Databases - Stochastic Data Mining. 1137-1152 - Boris Kovalerchuk, Evgenii Vityaev:
Data Mining for Financial Applications. 1153-1169 - Anoop Singhal, Sushil Jajodia:
Data Mining for Intrusion Detection. 1171-1180 - Kurt H. Thearling:
Data Mining for CRM. 1181-1188 - Nissan Levin, Jacob Zahavi:
Data Mining for Target Marketing. 1189-1220 - Oded Maimon, Abel Browarnik:
NHECD - Nano Health and Environmental Commented Database. 1221-1241
Part 8 / Software
- Qingyu Zhang, Richard S. Segall:
Commercial Data Mining Software. 1245-1268 - Eibe Frank, Mark Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer, Ian H. Witten, Len Trigg:
Weka-A Machine Learning Workbench for Data Mining. 1269-1277
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