On Classification from Outlier View

2009/07/29 by Ching-an Hsiao, C. A. Hsiao, Hsiao, C. A.
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Fuzzy Systems and Optimization #cs.AI

paper · pdf · doi:10.48550/arxiv.0907.5155

Conclusion renewed; IAENG International Journal of Computer Science, Volume 37, Issue 4, Nov, 2010

openalex publication_date 2009/07/29 · arxiv created 2012/01/02 · arxiv updated 2012/01/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Classification is the basis of cognition. Unlike other solutions, this study approaches it from the view of outliers. We present an expanding algorithm to detect outliers in univariate datasets, together with the underlying foundation. The expanding algorithm runs in a holistic way, making it a rather robust solution. Synthetic and real data experiments show its power. Furthermore, an application for multi-class problems leads to the introduction of the oscillator algorithm. The corresponding result implies the potential wide use of the expanding algorithm.

Citations

• Procedures for Detecting Outlying Observations in Samples
• Least squares quantization in PCM

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