Hussein Almuallim, Thomas G. Dietterich  Home/Search
Context Related
| orst.edu/pub/tgd/pape...aijfocus.ps.gz Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: orst.edu/~tgd/cv/pubs (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: In many domains, an appropriate inductive bias is the MIN-FEATURES bias, which prefers consistent hypotheses definable over as few features as possible. This paper defines and studies this bias in Boolean domains. First, it is shown that any learning algorithm implementing the MIN-FEATURES bias requires \Theta( 1 ffl ln 1 ffi + 1 ffl [2 p + p ln n]) training examples to guarantee PAC-learning a concept having p relevant features out of n available features. This bound is only... (Update)
Cited by: More
SOAP: Efficient Feature Selection of Numeric Attributes - Ruiz, Aguilar-Ruiz, Riquelme (2002) (Correct)
Fast Feature Ranking Algorithm - Ruiz, Riquelme, Aguilar-Ruiz (Correct)
Auto-Supervised Learning in the Bayesian Programming.. - Dangauthier.. (2005) (Correct)
Similar documents (at the sentence level):
21.6%: Efficient Algorithms for Identifying Relevant Features - Almuallim, Dietterich (1992) (Correct)
13.3%: Learning With Many Irrelevant Features - Almuallim, Dietterich (1991) (Correct)
Active bibliography (related documents): More All
0.8: Feature Selection for Classification - Dash, Liu (1997) (Correct)
0.5: Assessing the Importance of Features for Multi-Layer.. - Egmont-Petersen.. (1998) (Correct)
0.4: On Learning More Concepts - Hussein Almuallim (1992) (Correct)
Similar documents based on text: More All
0.7: New Structural Similarity Metrics for UML Models - Rufai (2003) (Correct)
0.4: The Alternating Step(r, s) Generator - Kanso (2002) (Correct)
0.4: Measuring Naira: a Symbolic Program with Irregular Parallelism - Junaidu, Trinder (2002) (Correct)
Related documents from co-citation: More All
26: Irrelevant Features and the Subset Selection Problem - John, Kohavi et al. - 1994
25: Programs for machine learning (context) - Quinlan - 1993
20: The feature selection problem: Traditional methods and a new algorithm (context) - Kira, Rendell
BibTeX entry: (Update)
Almuallim, H., & Dietterich, T. (1994). Learning Boolean Concepts in the Presence of Many Irrelevant Features. Artificial Intelligence, 69(1-2), 279--305. http://citeseer.ist.psu.edu/almuallim94learning.html More
@article{ almuallim94learning,
author = "Hussein Almuallim and Thomas G. Dietterich",
title = "Learning Boolean Concepts in the Presence of Many Irrelevant Features",
journal = "Artificial Intelligence",
volume = "69",
number = "1-2",
pages = "279-305",
year = "1994",
url = "citeseer.ist.psu.edu/almuallim94learning.html" }
Citations (may not include all citations):4212 Computers and Intractability: A Guide to the Theory of NP-Co.. (context) - Garey, Johnson - 1979
1359 Induction of Decision Trees (context) - Quinlan - 1986
465 Learnability and the VapnikChervonenkis Dimension (context) - Blumer, Ehrenfeucht et al. - 1989
317 Learning Quickly When Irrelevant Attributes Abound: A New Li.. (context) - Littlestone - 1988
274 Generalization as Search (context) - Mitchell - 1982
151 A General Lower Bound on the Number of Examples Needed for L.. (context) - Ehrenfeucht, Haussler et al. - 1988
149 Information Processing Letters (context) - Blumer, Ehrenfeucht et al. - 1987
147 Boolean Feature Discovery in Empirical Learning (context) - Pagallo, Haussler - 1990
139 A Greedy Heuristic For the Set Covering Problem (context) - Chvatal - 1979
125 Learning With Many Irrelevant Features - Almuallim, Dietterich - 1991
94 Learning in the Presence of Malicious Errors - Kearns, Li - 1988
74 A Branch and Bound Algorithm for Feature Subset Selection (context) - Narendra, Fukunaga - 1977
52 Learning from Good and Bad Data (context) - Laird - 1988
19 Efficient Algorithms for Identifying Relevant Features - Almuallim, Dietterich - 1992
16 Myths and legends in learning classification rules (context) - Buntine - 1990
11 Optimum Feature Selection by Zero-One Integer Programming (context) - Ichino, Sklansky - 1984
10 A Comparison of Seven Techniques for Choosing Subsets of Pat.. (context) - Mucciardi, Gose - 1971
5 Concept Coverage and Its Application to Two Learning Tasks (context) - Almuallim - 1992
4 Exploiting Symmetry Properties in the Evaluation of Inductiv.. (context) - Almuallim - 1991
4 Feature Selection for Linear Classifiers (context) - Ichino, Sklansky - 1984
2 On Feature Selection (context) - Queiros, Gelsma - 1984
2 A Mathematical Theory of Generalization: Parts I and II (context) - Wolpert - 1990
2 Computational Problems of Feature Selection Pertaining to La.. (context) - Kittler - 1980
1 Computational Complexity and VLSI Implementation of an Optim.. (context) - Morgera - 1986
The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.cs.orst.edu/~tgd/cv/pubs.html): More
An Experimental Comparison of the Nearest-Neighbor and.. - Wettschereck, Dietterich (1995) (Correct)
EDITORIAL Exploratory Research in Machine Learning - Exploratory Research (Correct)
Knowledge Compilation: Bridging the Gap between Specification.. - Dietterich (1991) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC