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» Evaluating learning algorithms and classifiers
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BMCBI
2006
99views more  BMCBI 2006»
15 years 3 months ago
Genetic algorithm learning as a robust approach to RNA editing site prediction
Background: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One f...
James Thompson, Shuba Gopal
EUSFLAT
2009
135views Fuzzy Logic» more  EUSFLAT 2009»
15 years 1 months ago
A Logic-Based Approach for Evaluating Interpretability of Fuzzy Rule-Based Classifiers
Abstract-- We describe an automatic approach for evaluating interpretability of fuzzy rule-based classifiers. The approach is based on the logical view of fuzzy rules, which are in...
Corrado Mencar, Ciro Castiello, Anna Maria Fanelli
135
Voted
ICPR
2008
IEEE
16 years 5 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
134
Voted
GIS
2009
ACM
15 years 8 months ago
Machine learning approach to report prioritization with an application to travel time dissemination
This paper looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn ...
Piotr Szczurek, Bo Xu, Jie Lin, Ouri Wolfson
122
Voted
CVPR
2008
IEEE
16 years 5 months ago
Boosting adaptive linear weak classifiers for online learning and tracking
Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Toufiq Parag, Fatih Porikli, Ahmed M. Elgammal