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Computer Science - Artificial Intelligence | Analysis of Rare Categories

Analysis of Rare Categories

He, Jingrui

2012, VIII, 136 p.

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  • First systematic investigation of rare categories
  • Suitable for researchers in the areas of data mining and feature selection
  • Develops effective algorithms with theoretical guarantees as well as good empirical results

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.

Content Level » Research

Keywords » Data analysis - Data mining - Feature selection - Machine learning - Majority class - Minority class - Rare category

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Database Management & Information Retrieval - Security and Cryptology

Table of contents 

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

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