Bayesian Network Classifier for Medical Data Analysis

Bayesian Network Classifier for Medical Data Analysis

Bayesian networks encode causal relations between variables using probability and graph theory. They can be used both for prediction of an outcome and interpretation of predictions based on the encoded causal relations. In this paper we analyse a tree-like Bayesian network learning algorithm optimised for classification of data and we give solutions to the interpretation and analysis of predict...

Best Bases Bayesian Hierarchical Classifier for Hyperspectral Data Analysis

Classification of hyperspectral data is challenging because of high dimensionality inputs coupled with possible high dimensional outputs and scarcity of labeled information. Previously, a multiclassifier system was formulated in a binary hierarchical framework to group classes for accurate, rapid discrimination. In order to improve performance for small sample sizes, a new approach was develope...

Bayesian Prediction in Spatial Data Analysis

CTBNCToolkit: Continuous Time Bayesian Network Classifier Toolkit

Continuous time Bayesian network classifiers are designed for temporal classification of multivariate streaming data when time duration of events matters and the class does not change over time. This paper introduces the CTBNCToolkit: an open source Java toolkit which provides a stand-alone application for temporal classification and a library for continuous time Bayesian network classifiers. C...

ABN: A Fast, Greedy Bayesian Network Classifier

Adaptive Bayes Network (ABN) is a fast algorithm for constructing Bayesian Network classifiers using Minimum Description Length (MDL) and automatic feature selection. ABN does well in domains where Naive Bayes fares poorly, and in other domains is, within statistical bounds, at least as good a classifier.