We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
A two-class imbalanced data problem (IDP) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. Though a discriminative...
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...