David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 11 (3):399-415 (2001)
Machine learning has been proven useful for solving the bottlenecks in building expert systems. Noise in the training instances will, however, confuse a learning mechanism. Two main steps are adopted here to solve this problem. The first step is to appropriately arrange the training order of the instances. It is well known from Psychology that different orders of presentation of the same set of training instances to a human may cause different learning results. This idea is used here for machine learning and an order arrangement scheme is proposed. The second step is to modify a conventional noise-free learning algorithm, thus making it suitable for noisy environment. The generalized version space learning algorithm is then adopted to process the training instances for deriving good concepts. Finally, experiments on the Iris Flower problem show that the new scheme can produce a good training order, allowing the generalized version space algorithm to have a satisfactory learning result
|Keywords||entropy machine learning noise training instance training order version space|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Tali Bitan & James R. Booth (2012). Offline Improvement in Learning to Read a Novel Orthography Depends on Direct Letter Instruction. Cognitive Science 36 (5):896-918.
Jeff Stickney (2008). Training and Mastery of Techniques in Wittgenstein's Later Philosophy: A Response to Michael Luntley. Educational Philosophy and Theory 40 (5):678-694.
Aviva Geva (2010). Ethical Aspects of Dual Coding. Journal of Business Ethics Education 7:5-24.
Patrick Ainley (2003). Towards a Seamless Web or a New Tertiary Tripartism? The Emerging Shape of Post-14 Education and Training in England. British Journal of Educational Studies 51 (4):390 - 407.
John A. Weber (2007). Business Ethics Training: Insights From Learning Theory. [REVIEW] Journal of Business Ethics 70 (1):61 - 85.
Tony Ghaye (1998). Teaching and Learning Through Critical Reflective Practice. D. Fulton Publishers.
Rosemary J. Stevenson (1998). Training Quality and Learning Goals: Towards Effective Learning for All. Behavioral and Brain Sciences 21 (3):426-427.
James Blackmon, David Byrd, Robert C. Cummins, Pierre Poirier & Martin Roth (2005). Atomistic Learning in Non-Modular Systems. Philosophical Psychology 18 (3):313-325.
Pierre Poirier (2005). Atomistic Learning in Non-Modular Systems. Philosophical Psychology 18 (3):313-325.
Kuo-Chin Chang, Tzung-Pei Hong & Shian-Shyong Tseng (1996). Machine Learning by Imitating Human Learning. Minds and Machines 6 (2):203-228.
Added to index2009-01-28
Total downloads27 ( #125,141 of 1,777,882 )
Recent downloads (6 months)1 ( #291,290 of 1,777,882 )
How can I increase my downloads?