LECTURE NOTES IN DATA MINING

LECTURE NOTES IN DATA MINING

CONTENTS


FRONT MATTER	i
POINT ESTIMATION ALGORITHMS Huadong Liu	1
APPLICATIONS OF BAYES THEOREM Erika Fuentes	15
SIMILARITY MEASURES Kevin E. Heinrich	27
DECISION TREES Olufemi A. Omitaomu	39
GENETIC ALGORITHMS Geoffrey Mazeroff	53
CLASSIFICATION: DISTANCE-BASED ALGORITHMS Zeqian Shen	67
DECISION TREE-BASED ALGORITHMS Farial Shahnaz	79
COVERING (RULE-BASED) ALGORITHMS Shakhina Pulatova	87
CLUSTERING: AN OVERVIEW Matthew Aldridge	99
CLUSTERING: HIERARCHICAL ALGORITHMS Huadong Liu	109
CLUSTERING: PARTITIONAL ALGORITHMS Kevin E. Heinrich	121
CLUSTERING: LARGE DATABASES Farial Shahnaz	133
CLUSTERING: CATEGORICAL ATTRIBUTES Olufemi A. Omitaomu	143
ASSOCIATION RULES: AN OVERVIEW Geoffrey Mazeroff	153
ASSOCIATION RULES: PARALLEL AND DISTRIBUTED ALGORITHMS Shakhina Pulatova	169
ASSOCIATION RULES: ADVANCED TECHNIQUES AND MEASURES Asim YarKhan	183
SPATIAL MINING: TECHNIQUES AND ALGORITHMS Matthew Aldridge	193
BACK MATTER	207
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