Analysis of Rare Categories

2012
ISBN: 978-3-642-22812-4
Verlag: Springer

Buch, Englisch, 136 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 389 g

Reihe: Cognitive Technologies

In many real-world problems, rare categories (minority classes) play essential roles despite their extreme scarcity. The discovery, characterization and prediction of rare categories of rare examples may protect us from fraudulent or malicious behavior, aid scientific discovery, and even save lives.

This book focuses on rare category analysis, where the majority classes have smooth distributions, and the minority classes exhibit the compactness property. Furthermore, it focuses on the challenging cases where the support regions of the majority and minority classes overlap. The author has developed effective algorithms with theoretical guarantees and good empirical results for the related techniques, and these are explained in detail. The book is suitable for researchers in the area of artificial intelligence, in particular machine learning and data mining.

Zielgruppe

Research

Autoren/Hrsg.

He, Jingrui

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Introduction.- Survey and Overview.- Rare Category Detection.- Rare Category Characterization.- Unsupervised Rare Category Analysis.- Conclusion and Future Directions.

Über Autor(innen)

Dr. Jingrui He received her PhD from Carnegie Mellon University. She is a researcher in the Machine Learning Group of the IBM T.J. Watson Research Center. Her research interests include rare category analysis, active learning, semisupervised learning, transfer learning and spam filtering.