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» Large-scale attribute selection using wrappers
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AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
15 years 3 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
ICML
2000
IEEE
15 years 10 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
DATAMINE
2002
125views more  DATAMINE 2002»
14 years 9 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
AAAI
2000
14 years 11 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock
CORR
2010
Springer
185views Education» more  CORR 2010»
14 years 9 months ago
Acdmcp: An adaptive and completely distributed multi-hop clustering protocol for wireless sensor networks
Clustering is a very popular network structuring technique which mainly addresses the issue of scalability in large scale Wireless Sensor Networks. Additionally, it has been shown...
Khalid Nawaz, Alejandro P. Buchmann