In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
The promotion analysis problem has been proposed in [16], where ranking-based promotion query processing techniques are studied to effectively and efficiently promote a given obje...