Abstract. In this paper, we propose a probabilistic approach to feature selection for multi-class text categorization. Specifically, we regard document class and occurrence of eac...
Ke Wu, Bao-Liang Lu, Masao Uchiyama, Hitoshi Isaha...
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
The paper presents and compares the data mining techniques for selection of the diagnostic features in the problem of blood cell recognition in leukemia. Different techniques are c...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
A major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. To reduce the dimension, a number of approaches based on rou...