Outlier Ensembles: An Introduction

ISBN-13: 9783319547640 / Angielski / Twarda / 2017 / 276 str.

Charu C. Aggarwal; Saket Sathe

Opis

This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification.

Spis treści

An Introduction to Outlier Ensembles.- Theory of Outlier Ensembles.- Variance Reduction in Outlier Ensembles.- Bias Reduction in Outlier Ensembles: The Guessing Game.- Model Combination Methods for Outlier Ensembles.- Which Outlier Detection Algorithm Should I Use?

O autorze

Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science  from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 300 papers in refereed conferences and journals, and has applied for or been granted more than 80 patents. He is author or editor of 16 books, including  textbooks on data mining, recommender systems, and outlier analysis. Because of the commercial value of his  patents, he  has thrice been designated a  Master Inventor at IBM. He has received several internal and external awards, including the EDBT  Test-of-Time Award (2014) and the IEEE ICDM Research Contributions Award (2015). He has also served as program or general chair of many major conferences  in data mining. He is a fellow of the  SIAM, ACM, and the IEEE, for ‘”contributions to knowledge discovery and data mining algorithms.”

Saket Sathe has worked at IBM Research  (Australia/United States) since 2013. Saket received a Ph.D. degree in Computer Science from EPFL (Lausanne) in 2013. Before that he received a Master's (M.Tech.)  degree in Electrical Engineering from the Indian Institute of Technology at Bombay and also spent one year working for a startup. His primary areas of interest are data mining and data management. Saket has served on program committees of several top-ranked conferences and has been invited to review papers for prominent peer-reviewed journals. His research has led to more than 20 papers and 5 patents. His work on sensor data management received the runner-up best-paper award in IEEE CollaborateCom 2014. He is a member of the ACM, IEEE, and the SIAM.