Abstract. This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds ’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same com-plexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.
Recent work in supervised learning has shown that a surpris-ingly simple Bayesian classifier with st...
We introduce a Bayesian network classifier less restrictive than Naive Bayes (NB) and Tree Augmented...
Naive Bayes (NB) is a simple but powerful tool for data classification. It is widely used in classif...
\u3cp\u3eThis work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) c...
This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier...
This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bay...
Abstract. The naive Bayesian classifier is a simple and effective classification method, which assum...
\u3cp\u3eThis work presents a new general purpose classifier named Averaged Extended Tree Augmented ...
The original publication is available at www.springerlink.comIn this paper we present several Bayesi...
The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the...
Bayesian classiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent perf...
Tree augmented naive Bayes is a semi-naive Bayesian Learning method. It relaxes the naive Bayes attr...
We present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. TANC mode...
AbstractWe present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. T...
. Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with s...
Recent work in supervised learning has shown that a surpris-ingly simple Bayesian classifier with st...
We introduce a Bayesian network classifier less restrictive than Naive Bayes (NB) and Tree Augmented...
Naive Bayes (NB) is a simple but powerful tool for data classification. It is widely used in classif...
\u3cp\u3eThis work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) c...
This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier...
This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bay...
Abstract. The naive Bayesian classifier is a simple and effective classification method, which assum...
\u3cp\u3eThis work presents a new general purpose classifier named Averaged Extended Tree Augmented ...
The original publication is available at www.springerlink.comIn this paper we present several Bayesi...
The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the...
Bayesian classiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent perf...
Tree augmented naive Bayes is a semi-naive Bayesian Learning method. It relaxes the naive Bayes attr...
We present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. TANC mode...
AbstractWe present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. T...
. Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with s...
Recent work in supervised learning has shown that a surpris-ingly simple Bayesian classifier with st...
We introduce a Bayesian network classifier less restrictive than Naive Bayes (NB) and Tree Augmented...
Naive Bayes (NB) is a simple but powerful tool for data classification. It is widely used in classif...