Small-sample error estimation: mythology versus mathematics

Ulisses Braga-Neto

doi:10.1117/12.619331

30 August 2005 Small-sample error estimation: mythology versus mathematics

Ulisses Braga-Neto

Proceedings Volume 5916, Mathematical Methods in Pattern and Image Analysis; 59160V (2005) https://doi.org/10.1117/12.619331
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Error estimation is a key aspect of statistical pattern recognition. The true classification error rate is usually unavailable since it depends on the unknown feature-label distribution. Hence, one needs to estimate the error rate from the available sample data. This paper presents a concise, mathematically rigorous review of the subject of error estimation in statistical pattern recognition, pointing to the pitfalls that arise in small-sample settings due to the use of "rules of thumb" and a neglect for proper mathematical understanding of the problem.

Citation Download Citation

Ulisses Braga-Neto "Small-sample error estimation: mythology versus mathematics", Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 59160V (30 August 2005); https://doi.org/10.1117/12.619331

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available