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» An Empirical Study of Regression Test Selection Techniques
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NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 9 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
ESANN
2000
13 years 10 months ago
A statistical model selection strategy applied to neural networks
In statistical modelling, an investigator must often choose a suitable model among a collection of viable candidates. There is no consensus in the research community on how such a...
Joaquín Pizarro Junquera, Elisa Guerrero V&...

Lecture Notes
742views
15 years 7 months ago
Computer Systems Analysis
Comparing systems using measurement, simulation, and queueing models. Common mistakes and how to avoid them, selection of techniques and metrics, art of data presentation, summariz...
Raj Jain
APIN
1998
132views more  APIN 1998»
13 years 9 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon
ICTIR
2009
Springer
14 years 3 months ago
"A term is known by the company it keeps": On Selecting a Good Expansion Set in Pseudo-Relevance Feedback
Abstract. It is well known that pseudo-relevance feedback (PRF) improves the retrieval performance of Information Retrieval (IR) systems in general. However, a recent study by Cao ...
Raghavendra Udupa, Abhijit Bhole, Pushpak Bhattach...