Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes
Sign Up to like & getrecommendations! Published in 2018 at "Machine Learning"
DOI: 10.1007/s10994-018-5718-0
Abstract: This paper introduces a novel parameter estimation method for the probability tables of Bayesian network classifiers (BNCs), using hierarchical Dirichlet processes (HDPs). The main result of this paper is to show that improved parameter estimation… read more here.
Keywords: hierarchical dirichlet; estimation; bayesian network; parameter estimation ... See more keywords
Improving Neural-Network Classifiers Using Nearest Neighbor Partitioning
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2016.2580570
Abstract: This paper presents a nearest neighbor partitioning method designed to improve the performance of a neural-network classifier. For neural-network classifiers, usually the number, positions, and labels of centroids are fixed in partition space before training.… read more here.
Keywords: nearest neighbor; network; network classifiers; neighbor partitioning ... See more keywords