2712 search results - page 378 / 543 » On learning algorithm selection for classification |
DIS
2006
Springer
15 years 4 months ago
2006
Springer
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
109
Voted
EUROCAST
2007
Springer
15 years 7 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
103
Voted
IWANN
1999
Springer
15 years 5 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
136
click to vote
AAAI
2010
15 years 2 months ago
2010
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
138
click to vote
MIR
2004
ACM
15 years 6 months ago
2004
ACM
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...