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84
Voted
ESANN
2006
14 years 10 months ago
Learning Visual Invariance
Invariance is a necessary feature of a visual system able to recognize real objects in all their possible appearance. It is also the processing step most problematic to understand ...
Alessio Plebe
ESANN
2006
14 years 10 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
87
Voted
IJCNN
2006
IEEE
15 years 2 months ago
Bimodal Integration of Phonemes and Letters: an Application of Multimodal Self-Organizing Networks
— Multimodal integration of sensory information has clear advantages for survival: events that can be sensed in more than one modality are detected more quickly and accurately, a...
Lennart Gustafsson, Andrew P. Paplinski
83
Voted
IJCNN
2006
IEEE
15 years 2 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
ESANN
2006
14 years 10 months ago
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
Aloísio Carlos de Pina, Gerson Zaverucha
Neural Networks
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