We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comp...
The paper presents a visualization-based approach to explore large databases of geographic metadata. The aim of the data exploration is to search and acquire expressive geographic...
Riccardo Albertoni, Alessio Bertone, Monica De Mar...
We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
One of the problems of Knowledge Discovery in Databases (KDD) is the lack of user support for solving KDD problems. Current Data Mining (DM) systems enable the user to manually des...
We investigate the following data mining problem from Computational Chemistry: From a large data set of compounds, find those that bind to a target molecule in as few iterations o...