2200 search results - page 19 / 440 » Objective reduction using a feature selection technique |
ISDA
2010
IEEE
13 years 7 months ago
2010
IEEE
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
PPSN
2010
Springer
13 years 7 months ago
2010
Springer
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
CEC
2010
IEEE
13 years 10 months ago
2010
IEEE
This work explores the use of clustering objectives in a Multi-Objective Genetic Algorithm (MOGA) for both, feature selection and cluster count optimization, under the application...
ICC
2007
IEEE
14 years 3 months ago
2007
IEEE
— Selected mapping (SLM) is a well-known method for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. The main drawbac...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...