Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
In this paper, we describe a new approach for color texture classification by use of Haralick features extracted from color co-occurrence matrices. As the color of each pixel can ...
Alice Porebski, Nicolas Vandenbroucke, Ludovic Mac...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...