Theoretical sampling for data mining

Tsau Young Lin

doi:10.1117/12.381733

6 April 2000 Theoretical sampling for data mining

Tsau Young Lin

Proceedings Volume 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II; (2000) https://doi.org/10.1117/12.381733
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

Given a finite sequence of vectors (numerical tuples), there is a complexity associated to it, called data complexity. The 'simplest' pattern that is supported by this data set has a complexity, called pattern complexity. Then the 'smallest' sub-sequence, whose pattern complexity and data complexity are both equal to the pattern complexity of the original sequence, is the smallest sample, called theoretical sample. This paper investigates such samples.

Citation Download Citation

Tsau Young Lin "Theoretical sampling for data mining", Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); https://doi.org/10.1117/12.381733

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