Particle Swarm Optimisation for learning Bayesian Networks
نویسندگان
چکیده
Specifically, we detail two methods which adopt the search and score approach to BN learning. The two algorithms are similar in that they both use PSO as the search algorithm, and the K2 metric to score the resulting network. The difference lies in the way networks are constructed. The CONstruct And Repair (CONAR) algorithm generates structures, validates, and repairs if required, and the REstricted STructure (REST) algorithm, only permits valid structures to be developed. Initial experiments indicate that these approaches produce promising results when compared to other BN learning strategies.
منابع مشابه
Learning of B-spline Neural Network Using New Particle Swarm Approaches
New approaches of particle swarm optimisation algorithm based on Gaussian and Cauchy distributions to adjust the control points of B-spline neural networks are proposed. B-spline networks are trained by gradient-based methods, which may fall into local minimum during the learning procedure. To overcome the problems encountered by the conventional learning methods, particle swarm optimisation ...
متن کاملA survey on computational intelligence approaches for predictive modeling in prostate cancer
Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex for conventional statistical techniques to process quickly and efficiently. These advanced approaches ...
متن کاملAdaptive Particle Swarm Optimisation for High-Dimensional Highly Convex Search Spaces
The Particle Swarm Optimisation (PSO) algorithm has been established as a useful global optimisation algorithm for multi-dimensional search spaces. A practical example is its success in training feed-forward neural networks. Such successes, however, must be judged relative to the complexity of the search space. In this paper we show that the effectiveness of the PSO algorithm breaks down when e...
متن کاملOptimal Placement and Sizing of DGs and Shunt Capacitor Banks Simultaneously in Distribution Networks using Particle Swarm Optimization Algorithm Based on Adaptive Learning Strategy
Abstract: Optimization of DG and capacitors is a nonlinear objective optimization problem with equal and unequal constraints, and the efficiency of meta-heuristic methods for solving optimization problems has been proven to any degree of complex it. As the population grows and then electricity consumption increases, the need for generation increases, which further reduces voltage, increases los...
متن کاملA Particle Swarm Optimization and Immune Theory-Based Algorithm for Structure Learning of Bayesian Networks
Bayesian network is a directed acyclic graph. Existing Bayesian network learning approaches based on search & scoring usually work with a heuristic search for finding the highest scoring structure. This paper describes a new data mining algorithm to learn Bayesian networks structures based on an immune binary particle swarm optimization (IBPSO) method and the Minimum Description Length (MDL) pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007