— One of the central problems for data quality is inconsistency detection. Given a database D and a set Σ of dependencies as data quality rules, we want to identify tuples in D ...
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...