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We evaluate the effectiveness of cross-validation in selecting the right-size model for decision tree and k-nearest neighbor learning methods. For samples with at least 200 cases, extensive empirical evidence supports the following conclusions relative to complexity-fit selection: (a) 10-fold...
A sigmoid Bayesian network is a Bayesian network in which a conditional probability is a sigmoid function of the weights of relevant arcs. Its application domain includes that of Boltzmann machine as well as traditional decision problems. In this paper we show that the node reduction method that...
In classical Constraint Satisfaction Problems (CSPs) knowledge is embedded in a set of hard constraints, each one restricting the possible values of a set of variables. However constraints in real world problems are seldom hard, and CSP's are often idealizations that do not account for the...
We develop here a logic % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9qq-f0-yqaqVeLsFr0-vr%...
With increasingly complex, sophisticated and changeable real-world domains, knowledge based systems have to cope with the problems of maintaining the consistency and the integrity of their knowledge bases. It is becoming increasingly important that knowledge base be formally verified. This...
In this paper, a greedy route construction heuristic for a vehicle routing problem with backhauling is described. This heuristic inserts customers one by one into the routes using a fixed a priori ordering of customers. Then, a genetic algorithm is used to identify an ordering that produces good...
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