A rule importance measure is used to evaluate how important are the rules which characterize a data set. This measure was designed based on association rules and it has been proven to be effective to enumerate the most important rules of all rules generated. However, since rule importance is an objective measure, its usage as a rule interestingness measure relies on the interpretation of domain...

In this paper, we introduce a new machine learning theory based on multi-channel parallel adaptation for rule discovery. This theory is distinguished from the familiar parallel-distributed adaptation theory of neural networks in terms of channel-based convergence to the target rules. We show how to realize this theory in a learning system named CFRule. CFRule is a parallel weight-based model, b...

Synaptic plasticity was recently shown to depend on the relative timing of the pre- and postsynaptic spikes. This article analytically derives a spike-dependent learning rule based on the principle of information maximization for a single neuron with spiking inputs. This rule is then transformed into a biologically feasible rule, which is compared to the experimentally observed plasticity. This...

In this paper, we introduce a new machine learning theory based on multi-channel parallel adaptation for rule discovery. This theory is distinguished from the familiar paralleldistributed adaptation theory of neural networks in terms of channel-based convergence to the target rules. We show how to realize this theory in a learning system named CFRule. CFRule is a parallel weight-based model, bu...

Drawing from recent theories of economic accountability that stress the contextual nature attributed responsibility, this paper explores how variation in regional authority influences interplay between objective conditions and perceived performance. The study uses a virtually unexplored set surveys about public opinion European Union regions broad sample politically decentralized democracies. r...

The existence and uniqueness of the Gaussian interval quadrature formula with respect to the Hermite weight function on R is proved. Similar results have been recently obtained for the Jacobi weight on [−1, 1] and for the generalized Laguerre weight on [0,+∞). Numerical construction of the Gauss–Hermite interval quadrature rule is also investigated, and a suitable algorithm is proposed. A few n...

The effect of different kinds of weight normalization on the outcome of a simple competitive learning rule is analysed. It is shown that there are important differences in the representation formed depending on whether the constraint is enforced by dividing each weight by the same amount (“divisive enforcement”), or subtracting a fixed amount from each weight (“subtractive enforcement”). For th...

Ranking has been widely used in many applications. A ranking scheme usually employs a "scoring rule" that assigns a final numerical value to each and every object to be ranked. A scoring rule normally involves the use of one to many scores, and it gives more weight to the scores that is more important. In this paper, we give a scheme that can combine weights into scores in a natural way. We com...

The 2013 Final Rule on major capital investment projects revised the measures that FTA uses to evaluate and rate proposed major transit projects. Among the revised measures, the Final Rule specifies that mobility benefits are now measured as the predicted number of trips that would use the project, with a weight of 2.0 applied to project trips that would be made by transit dependents. The Final...