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Advanced Techniques in Knowledge Discovery and Data Mining

:	Nikhil R. Pal, Lakhmi Jain
:	Nikhil Pal
:	Advanced Techniques in Knowledge Discovery and Data Mining
:	Springer-Verlag
:	9781846281839
:	1
:	CHF 89.50
:

:	Informatik
:	English

:	256
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Clear and concise explanations to understand the learning paradigms.

Chapters written by leading world experts.

	Contents	6
	Preface	7
	1. Trends in Data Mining and Knowledge Discovery	13
	1.1 Knowledge Discovery and Data Mining Process	13
	1.2 Six-Step Knowledge Discovery and Data Mining Process	17
	1.3 New Technologies	22
	1.4 Future of Data Mining and Knowledge Discovery?	28
	1.5 Conclusions	32
	Acknowledgments	33
	References	33
	2. Advanced Methods for the Analysis of Semiconductor Manufacturing Process Data	39
	2.1 Introduction	39
	2.2 Semiconductor Manufacturing and Data Acquisition	42
	2.3 Selected Soft-Computing Methods	52
	2.4 Experiments and Results	73
	2.5 Proposed System Architecture	80
	2.6 Conclusions	82
	Acknowledgments	83
	References	83
	3. Clustering and Visualization of Retail Market Baskets	87
	3.1 Introduction	87
	3.2 Domain-Speci.c Features and Similarity Space	91
	3.3 OPOSSUM	93
	3.4 CLUSION: Cluster Visualization	96
	3.5 Experiments	101
	3.6 System Issues	105
	3.7 Related Work	108
	3.8 Concluding Remarks	111
	References	112
	4. Segmentation of Continuous Data Streams Based on a Change Detection Methodology	115
	4.1 Introduction	115
	4.2 Change Detection in Classification Models	117
	4.3 Application Evaluation	124
	4.4 Conclusions and Future Work	133
	References	135
	5. Instance Selection Using Evolutionary Algorithms: An Experimental Study	139
	5.1 Introduction	139
	5.2 Instance Selection	141
	5.3 Survey of Instance Selection Algorithms	145
	5.4 Evolutionary Algorithms	147
	5.5 Evolutionary Instance Selection	151
	5.6 Methodology for the Experiments	153
	5.7 Analysis of the Experiments	157
	5.8 Concluding Remarks	161
	References	162
	6. Using Cooperative Coevolution for Data Mining of Bayesian Networks	165
	6.1 Introduction	165
	6.2 Background	167
	6.3 Learning Using Evolutionary Computation	172
	6.4 Proposed Algorithm	175
	6.5 Performance of CCGA	182
	6.6 Conclusion	185
	Acknowledgment	185
	7. Knowledge Discovery and Data Mining in Medicine	188
	7.1 Introduction	188
	7.2 KBANN with Structure Level Adaptation	189
	7.3 Rule Extraction by ADG	199
	7.4 Immune Multiagent Neural Networks	203
	7.5 Conclusion and Discussion	219
	References	220
	8. Satellite Image Classification Using Cascaded Architecture of Neural Fuzzy Network	222
	8.1 Introduction	222
	8.2 Input Acquisition	225
	8.3 A Cascaded Architecture of a Neural Fuzzy Network with Feature Mapping (CNFM)	230
	8.4 Experimental Results	237
	8.5 Conclusions	240
	8.6 References	241
	9. Discovery of Positive and Negative Rules from Medical Databases Based on Rough Sets	243
	9.1 Introduction	243
	9.2 Focusing Mechanism	244
	9.3 De.nition of Rules	245
	9.4 Algorithms for Rule Induction	251
	9.5 Experimental Results	251
	9.6 What Is Discovered?	254
	9.7 Rule Discovery as Knowledge Acquisition and Decision Support	257
	9.8 Discussion	258
	9.9 Conclusions	261
	References	261
	Index	263