7 search results - page 1 / 2 » Training and Testing Low-degree Polynomial Data Mappings via... |
JMLR
2010
12 years 11 months ago
2010
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
ML
2008
ACM
13 years 5 months ago
2008
ACM
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
NIPS
2004
13 years 6 months ago
2004
In this paper we show that it is possible to model sensory impressions of consumers about beef meat. This is not a straightforward task; the reason is that when we are aiming to i...
DATAMINE
1998
13 years 4 months ago
1998
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
DATAMINE
1999
13 years 4 months ago
1999
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...