Fisher score and Laplacian score are two popular feature selection algorithms, both of which belong to the general graph-based feature selection framework. In this framework, a fe...
Feiping Nie, Shiming Xiang, Yangqing Jia, Changshu...
Traditional information retrieval systems use query words to identify relevant documents. In difficult retrieval tasks, however, one needs access to a wealth of background knowled...
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
Elena Marchiori, Connie R. Jimenez, Mikkel West-Ni...
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Feature selection is a critical procedure in many pattern recognition applications. There are two distinct mechanisms for feature selection namely the wrapper methods and the filte...
Michal Haindl, Petr Somol, Dimitrios Ververidis, C...
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...