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Autor: Nikhil R. Pal, Lakhmi Jain
Herausgeber: Nikhil Pal
Titel: Advanced Techniques in Knowledge Discovery and Data Mining
Verlag: Springer-Verlag
ISBN/ISSN: 9781846281839
Auflage: 1
Preis : CHF 147.80
Erscheinungsdatum:
Inhalt
Kategorie: Informatik, EDV Buch
Sprache: English
Technische Daten
Seiten: 256
Kopierschutz: DRM
Geräte: PC/MAC/eReader/Tablet
Formate: PDF
Inhaltsangabe

Clear and concise explanations to understand the learning paradigms.


Chapters written by leading world experts.

Inhaltsverzeichnis
Contents6
Preface7
1. Trends in Data Mining and Knowledge Discovery13
1.1 Knowledge Discovery and Data Mining Process13
1.2 Six-Step Knowledge Discovery and Data Mining Process17
1.3 New Technologies22
1.4 Future of Data Mining and Knowledge Discovery?28
1.5 Conclusions32
Acknowledgments33
References33
2. Advanced Methods for the Analysis of Semiconductor Manufacturing Process Data39
2.1 Introduction39
2.2 Semiconductor Manufacturing and Data Acquisition42
2.3 Selected Soft-Computing Methods52
2.4 Experiments and Results73
2.5 Proposed System Architecture80
2.6 Conclusions82
Acknowledgments83
References83
3. Clustering and Visualization of Retail Market Baskets87
3.1 Introduction87
3.2 Domain-Speci.c Features and Similarity Space91
3.3 OPOSSUM93
3.4 CLUSION: Cluster Visualization96
3.5 Experiments101
3.6 System Issues105
3.7 Related Work108
3.8 Concluding Remarks111
References112
4. Segmentation of Continuous Data Streams Based on a Change Detection Methodology115
4.1 Introduction115
4.2 Change Detection in Classification Models117
4.3 Application Evaluation124
4.4 Conclusions and Future Work133
References135
5. Instance Selection Using Evolutionary Algorithms: An Experimental Study139
5.1 Introduction139
5.2 Instance Selection141
5.3 Survey of Instance Selection Algorithms145
5.4 Evolutionary Algorithms147
5.5 Evolutionary Instance Selection151
5.6 Methodology for the Experiments153
5.7 Analysis of the Experiments157
5.8 Concluding Remarks161
References162
6. Using Cooperative Coevolution for Data Mining of Bayesian Networks165
6.1 Introduction165
6.2 Background167
6.3 Learning Using Evolutionary Computation172
6.4 Proposed Algorithm175
6.5 Performance of CCGA182
6.6 Conclusion185
Acknowledgment185
7. Knowledge Discovery and Data Mining in Medicine188
7.1 Introduction188
7.2 KBANN with Structure Level Adaptation189
7.3 Rule Extraction by ADG199
7.4 Immune Multiagent Neural Networks203
7.5 Conclusion and Discussion219
References220
8. Satellite Image Classification Using Cascaded Architecture of Neural Fuzzy Network222
8.1 Introduction222
8.2 Input Acquisition225
8.3 A Cascaded Architecture of a Neural Fuzzy Network with Feature Mapping (CNFM)230
8.4 Experimental Results237
8.5 Conclusions240
8.6 References241
9. Discovery of Positive and Negative Rules from Medical Databases Based on Rough Sets243
9.1 Introduction243
9.2 Focusing Mechanism244
9.3 De.nition of Rules245
9.4 Algorithms for Rule Induction251
9.5 Experimental Results251
9.6 What Is Discovered?254
9.7 Rule Discovery as Knowledge Acquisition and Decision Support257
9.8 Discussion258
9.9 Conclusions261
References261
Index263