We propose Genetic Algorithms to improve the feature subset selection by combining the valuable outcomes from multiple feature selection methods. This paper also motivates the use...
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
By analogy with merging documents rankings, the outputs from multiple search results clustering algorithms can be combined into a single output. In this paper we study the feasibi...
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
Background: There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large,...