JMLR
2012
11 years 7 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
JGO
2011
12 years 7 months ago
2011
Abstract In many problems from different disciplines such as engineering, physics, medicine, and biology, a series of experimental data is used in order to generate a model that ca...
BMCBI
2011
12 years 8 months ago
2011
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
BMCBI
2008
13 years 4 months ago
2008
Background: Predictive classification on the base of gene expression profiles appeared recently as an attractive strategy for identifying the biological functions of genes. Gene O...
SDM
2008
SIAM
13 years 5 months ago
2008
SIAM
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
ICML
1994
IEEE
13 years 8 months ago
1994
IEEE
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
COLT
1995
Springer
13 years 8 months ago
1995
Springer
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
KDD
2007
ACM
14 years 4 months ago
2007
ACM
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...