1090 search results - page 39 / 218 » A Support Vector Machine Approach for Detection of Microcalc... |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
JMLR
2008
13 years 7 months ago
2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
NIPS
2004
13 years 9 months ago
2004
The standard approach to the classification of objects is to consider the examples as independent and identically distributed (iid). In many real world settings, however, this ass...
PR
2006
13 years 7 months ago
2006
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
ALT
2000
Springer
14 years 4 months ago
2000
Springer
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...