12 years 10 months ago
Disaggregated End-Use Energy Sensing for the Smart Grid
Most utility installed energy meters are primarily intended to support a utility's billing function. They report only the aggregate energy consumption of a home or business o...
Jon Froehlich, Eric Larson, Sidhant Gupta, Gabe Co...
104views more  JMLR 2010»
13 years 2 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
13 years 5 months ago
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
Frank G. Glavin, Michael G. Madden
85views more  JVCIR 2006»
13 years 7 months ago
Combining geometrical and textured information to perform image classification
In this paper, we propose a framework to carry out supervised classification of images containing both textured and non textured areas. Our approach is based on active contours. U...
Jean-François Aujol, Tony F. Chan
156views more  COMSIS 2006»
13 years 7 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
13 years 8 months ago
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification
We propose a novel approach that reduces cost-sensitive classification to one-sided regression. The approach stores the cost information in the regression labels and encodes the m...
Han-Hsing Tu, Hsuan-Tien Lin
13 years 8 months ago
Using sampling methods to improve binding site predictions
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. In previous work we combine random selection under-sampling with th...
Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhors...
13 years 9 months ago
A modeling-based classification algorithm validated with simulated data
We present a Generalized Lotka-Volterra (GLV) based approach for modeling and simulation of supervised inductive learning, and construction of an efficient classification algorith...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
13 years 9 months ago
Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Jason Chan, Josiah Poon, Irena Koprinska
143views Database» more  DEXA 2006»
13 years 11 months ago
Multivariate Stream Data Classification Using Simple Text Classifiers
We introduce a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes as input a sliding wi...
Sungbo Seo, Jaewoo Kang, Dongwon Lee, Keun Ho Ryu