Introduction to Data Mining - by Camila Thompson (Hardcover)

About the Book

Data mining is a process which deals with the discovery of patterns in large data sets. It applies methods from the fields of statistics, database systems and machine learning. Data mining aims to transform the information derived from a data set into a comprehensible structure for further use. Data mining also includes the data management aspects, complexity considerations, visualization, online updating, data pre-processing, model and inference considerations, and post-processing of discovered structures. It uses statistical models and machine-learning to uncover hidden patterns in a large volume of data. There are numerous fields where it is applied such as business, medicine, surveillance and science. This book aims to shed light on some of the unexplored aspects of data mining. Such selected concepts that redefine data mining have been presented herein. For someone with an interest and eye for detail, this book covers the most significant topics in this field.

Book Synopsis

Data mining is a process which deals with the discovery of patterns in large data sets. It applies methods from the fields of statistics, database systems and machine learning. Data mining aims to transform the information derived from a data set into a comprehensible structure for further use. Data mining also includes the data management aspects, complexity considerations, visualization, online updating, data pre-processing, model and inference considerations, and post-processing of discovered structures. It uses statistical models and machine-learning to uncover hidden patterns in a large volume of data. There are numerous fields where it is applied such as business, medicine, surveillance and science. This book aims to shed light on some of the unexplored aspects of data mining. Such selected concepts that redefine data mining have been presented herein. For someone with an interest and eye for detail, this book covers the most significant topics in this field.