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» Evaluating learning algorithms and classifiers
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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 5 months ago
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
Vincent Yan Fu Tan, See-Kiong Ng
152
Voted
HIS
2004
15 years 6 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
167
Voted
CLEF
2010
Springer
15 years 5 months ago
Combination of Classifiers for Indoor Room Recognition CGS participation at ImageCLEF2010 Robot Vision Task
This paper represents a description of our approach to the problem of topological localization of a mobile robot using visual information. Our method has been developed for ImageCL...
Walter Lucetti, Emanuel Luchetti
145
Voted
BMCBI
2010
161views more  BMCBI 2010»
15 years 2 months ago
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers
Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of ...
Mohammed Dakna, Keith Harris, Alexandros Kalousis,...
161
Voted
SAC
2010
ACM
14 years 11 months ago
A new methodology for photometric validation in vehicles visual interactive systems
This work proposes a new methodology for automatically validating the internal lighting system of an automotive, i.e., assessing the visual quality of an instrument cluster (IC) f...
Alexandre W. C. Faria, David Menotti, Daniel S. D....