We discuss the weight update rule in the Cascade Correlation neural net learning algorithm. The weight update rule implements gradient descent optimization of the correlation between a new hidden unit's output and the previous network's error. We present a derivation of the gradient of the correlation function and show that our resulting weight update rule results in slightly faster training. W...

Association rule mining play important rule in market data analysis and also in medical diagnosis of correlated problem. For the generation of association rule mining various technique are used such as Apriori algorithm, FP-growth and tree based algorithm. Some algorithms are wonder performance but generate negative association rule and also suffered from Superiority measure problem. In this pa...

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results sho...

A conditional spatial autoregression (CAR) specifies dependence via a weight matrix. Employing a doubly stochastic weight matrix allows users to interpret the CAR prediction rule as a semiparametric prediction rule and as BLUP with smoothing in addition to other benefits. We examine standard and doubly stochastic weight matrices in the context of an illustrative data set to demonstrate feasibil...

Various rules have been proposed to identify and exclude live births with implausible values of birth weight for gestational age from large perinatal data sets. The authors carried out a preliminary evaluation of common rules by examining the frequency and nature of rule-based exclusions among live births in Canada (excluding Ontario) between 1992 and 1994. There were 625 (0.09%), 133 (0.02%), ...