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» Design Pattern Mining Enhanced by Machine Learning
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AIR
2004
113views more  AIR 2004»
13 years 7 months ago
Class Noise vs. Attribute Noise: A Quantitative Study
Real-world data is never perfect and can often suffer from corruptions (noise) that may impact interpretations of the data, models created from the data and decisions made based on...
Xingquan Zhu, Xindong Wu
CIKM
2009
Springer
13 years 11 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
WACV
2007
IEEE
14 years 2 months ago
A Vision System for Monitoring Intermodal Freight Trains
We describe the design and implementation of a vision based Intermodal Train Monitoring System(ITMS) for extracting various features like length of gaps in an intermodal(IM) train...
Avinash Kumar, Narendra Ahuja, John M. Hart, Vises...
MLDM
2005
Springer
14 years 1 months ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé
KDD
2006
ACM
201views Data Mining» more  KDD 2006»
14 years 8 months ago
Clustering based large margin classification: a scalable approach using SOCP formulation
This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture...
J. Saketha Nath, Chiranjib Bhattacharyya, M. Naras...