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» Regression with interval output values
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NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 7 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
IWANN
1999
Springer
13 years 11 months ago
Paradoxical Relationship between Output and Input Regularity for the FitzHugh-Nagumo Model
Abstract. We examine the effects of changing the coefficient of variation (CV) of the inter-stimulus interval on the CV of the output interspike interval (ISI), using constant magn...
Stuart Feerick, Jianfeng Feng, David Brown
COLT
2006
Springer
13 years 11 months ago
Active Sampling for Multiple Output Identification
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Eff...
Shai Fine, Yishay Mansour
AMC
2006
173views more  AMC 2006»
13 years 7 months ago
Data envelopment analysis with missing values: An interval DEA approach
Missing values in inputs, outputs cannot be handled by the original data envelopment analysis (DEA) models. In this paper we introduce an approach based on interval DEA that allow...
Yannis G. Smirlis, Elias K. Maragos, Dimitris K. D...
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 11 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
Cassio Pennachin, Moshe Looks, João A. de V...