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» On learning algorithm selection for classification
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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 6 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
14 years 15 days ago
Applicability issues of the real-valued negative selection algorithms
The paper examines various applicability issues of the negative selection algorithms (NSA). Recently, concerns were raised on the use of NSAs, especially those using real-valued r...
Zhou Ji, Dipankar Dasgupta
ECML
2006
Springer
14 years 16 days ago
Cost-Sensitive Decision Tree Learning for Forensic Classification
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
WWW
2004
ACM
14 years 9 months ago
Dynamic assembly of learning objects
This paper describes one solution to the problem of how to select sequence, and link Web resources into a coherent, focused organization for instruction that addresses a user'...
Robert G. Farrell, Soyini D. Liburd, John C. Thoma...
JMLR
2006
79views more  JMLR 2006»
13 years 8 months ago
Estimation of Gradients and Coordinate Covariation in Classification
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
Sayan Mukherjee, Qiang Wu