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» On the Network Complexity of Selection
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AIME
2009
Springer
15 years 10 months ago
The Role of Biomedical Dataset in Classification
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...
Ajay Kumar Tanwani, Muddassar Farooq
NECO
2002
78views more  NECO 2002»
15 years 6 months ago
Local Overfitting Control via Leverages
We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
Gaétan Monari, Gérard Dreyfus
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICANN
2010
Springer
15 years 4 months ago
The Support Feature Machine for Classifying with the Least Number of Features
We propose the so-called Support Feature Machine (SFM) as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyperplan...
Sascha Klement, Thomas Martinetz
PRL
2007
180views more  PRL 2007»
15 years 6 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...