Transcription of Data Mining Concepts and Techniques (3rd ed.)
{{id}} {{{paragraph}}}
Example: biology
Data Mining Concepts and Techniques (3rd ed.)
Table of Contents Cover Image Front Matter Copyright Dedication Foreword Foreword to Second Edition Preface Acknowledgments About the Authors 1. Introduction Why data Mining ? What Is data Mining ? What Kinds of data Can Be Mined? What Kinds of Patterns Can Be Mined? Which Technologies Are Used? Which Kinds of Applications Are Targeted? Major Issues in data Mining Summary Exercises Bibliographic Notes 2. Getting to Know Your data data Objects and Attribute Types Basic Statistical Descriptions of data data visualization Measuring data Similarity and Dissimilarity Summary Exercises Bibliographic Notes 3. data Preprocessing data Preprocessing: An Overview data Cleaning data Integration data Reduction data Transformation and data Discretization Summary Exercises Bibliographic Notes 4.
Multidimensional Data Analysis in Cube Space 5.5. Summary 5.6. Exercises 5.7. Bibliographic Notes 6. Mining Frequent Patterns, Associations, and Correlations ... Information Visualization in Data Mining and KnowledgeDiscovery Edited by Usama Fayyad, Georges G. …
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: