内容

目次

Introduction to knowledge discovery in databases.- Part I Preprocessingmethods.- Data cleansing.- Handling missing attribute values.- Geometricmethods for feature extraction and dimensional reduction.- DimensionReduction and feature selection.- Discretization methods.- outlierdetection.- Part II Supervised methods.- Introduction to supervised methods.-Decision trees.- Bayesian networks.- Data mining within a regressionframework.- Support vector machines.- Rule induction.- Part III Unsupervisedmethods.- Visualization and data mining for high dimensional datasets.-Clustering methods.- Association rules.- Frequent set mining.-Constraint-based data mining.- Link analysis.- Part IV Soft computingmethods.- Evolutionary algorithms for data mining.- Reinforcement-learning:an overview from a data mining perspective.- Neural networks.- On the use offuzzy logic in data mining.- Granular computing and rough sets.- Part VSupporting methods.- Statistical methods for data mining.- Logics for datamining.- Wavelet methods in data mining.- Fractal mining.- Interestingnessmeasures.- Quality assessment approaches in data mining.- Data mining modelcomparison.- Data mining query languages.- Part VI Advanced methods.-Meta-learning.- Bias vs variance decomposition for regression andclassification.- Mining with rare cases.- Mining data streams.- Mininghigh-dimensional data.- Text mining and information extraction.- Spatial datamining.- Data mining for imbalanced datasets: an overview.- Relational datamining.- Web mining.- A review of web document clustering approaches.- Causaldiscovery.- Ensemble methods for classifiers.- Decomposition methodology forknowledge discovery and data mining.- Information fusion.- Parallel andgrid-based data mining.- Collaborative data mining.- Organizational datamining.- Mining time series data.- Part VII Applications.- Data mining inmedicine.- Learning information patterns in biological databases.- Datamining for selection of manufacturing processes.- Data mining of designproducts and processes.- Data mining in telecommunications.- Data mining forfinancial applications.- Data mining for intrusion detection.- Data miningfor software testing.- Data mining for CRM.- Data mining for targetmarketing.- Part VIII Software.- Oracle data mining.- Building data miningsolutions with OLE DB for DM and XML for analysis.- LERSoA data miningsystem.- GainSmarts data mining system for marketing.- WizSoft's WizWhy.-DataEngine.- Index.