Ernest Monga

Learn More
Clustering categorical data poses two challenges defining an inherently meaningful similarity measure, and effectively dealing with clusters which are often embedded in different subspaces. In this paper, we propose a novel divisive hierarchical clustering algorithm for categorical data, named DHCC. We view the task of clustering categorical data from an(More)
Clustering categorical data faces two challenges, one is lacking of inherent similarity measure, and the other is that the clusters are prone to being embedded in different subspace. In this paper, we propose the first divisive hierarchical clustering algorithm for categorical data. The algorithm, which is based on Multiple Correspondence Analysis (MCA), is(More)
A personal bankruptcy prediction system running on credit card data is proposed. Personal bankruptcy, which usually results in significant losses to creditors, is a rapidly increasing yet little understood phenomenon. The most commonly used methods in personal bankruptcy prediction are credit scoring models. Some data mining models have also been(More)
Vascular plants are commonly colonized by endophytic actinobacteria. However, very little is known about the relationship between these microorganisms and cacao fruits. In order to determine the physiological and taxonomic relationships between the members of this community, actinobacteria were isolated from cacao fruits and seeds. Among the 49 isolates(More)
Potato peels consist of a tissue called phellem, which is formed by suberized cell layers. The degradation of suberin, a lipidic and recalcitrant polymer, is an ecological process attributed to soil fungal populations; however, previous studies have suggested that Streptomyces scabiei, the causal agent of potato common scab, possesses the ability to degrade(More)
We propose a new efficient algorithm for solving the cluster labeling problem in support vector clustering (SVC). The proposed algorithm analyzes the topology of the function describing the SVC cluster contours and explores interconnection paths between critical points separating distinct cluster contours. This process allows distinguishing disjoint(More)
After decades of refinement, DNA testing methods have become essential tools in forensic sciences. They are essentially based on likelihood ratio test principle, which is utilized specifically, by using as prior knowledge the allele frequencies in the population, to confirm or refute a given kinship hypothesis made on two genotypes. This makes these methods(More)
  • 1