The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Many knowledge representation mechanisms are based on tree-like structures, thus symbolizing the fact that certain pieces of information are related in one sense or another. There ...
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
: The paper proposes a different approach to data modeling. Analogous to the rejection method, where the misclassifications are removed and manually evaluated, we focus here on dif...