18 search results - page 1 / 4 » Selection of important input variables for RBF network using... |
ESANN
2008
13 years 6 months ago
2008
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Input selection in the nonlinear function approximation is important and difficult problem. Neural networks provide good generalization in many cases, but their interpretability is...
NCA
2002
IEEE
13 years 4 months ago
2002
IEEE
One of the key problems in forming a smooth model from input-output data is the determination of which input variables are relevant in predicting a given output. In this paper we ...
AUSAI
2007
Springer
13 years 8 months ago
2007
Springer
Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (gen...
ICPR
2000
IEEE
14 years 5 months ago
2000
IEEE
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...