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» Bootstrap for neural model selection
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SSPR
2004
Springer
14 years 3 months ago
An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
MOBIQUITOUS
2007
IEEE
14 years 4 months ago
TRULLO - local trust bootstrapping for ubiquitous devices
—Handheld devices have become sufficiently powerful that it is easy to create, disseminate, and access digital content (e.g., photos, videos) using them. The volume of such cont...
Daniele Quercia, Stephen Hailes, Licia Capra
ESANN
2008
13 years 11 months ago
A multiple testing procedure for input variable selection in neural networks
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
Michele La Rocca, Cira Perna
ICMLC
2010
Springer
13 years 7 months ago
Optimization of bagging classifiers based on SBCB algorithm
: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
Xiao-Dong Zeng, Sam Chao, Fai Wong
SBRN
2008
IEEE
14 years 4 months ago
Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach
In this work, we propose to use the Zoomed-Ranking approach to ranking and selecting Artificial Neural Network (ANN) models for time series forecasting. Given a time series to fo...
Patrícia M. Santos, Teresa Bernarda Ludermi...