Add to ORKGThe task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework and using various mathematical and algorithmic approximations, the AutoClass system searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit or share model parameters though a...
Algorithms for learning classification trees have had successes in artificial intelligence and stati...
A criterion, based on Bayes' theorem, is described that defines the optimal set of classes (a classi...
The na ve Bayes classifier is built on the assumption of conditional independence between the attrib...
The task of inferring a set of classes and class descriptions most likely to explain a given data se...
In 1983 and 1984, the Infrared Astronomical Satellite (IRAS) detected 5,425 stellar objects and meas...
The naïve Bayes classifier is built on the assumption of conditional independence between the attrib...
Recently, several theoretical and applied studies have shown that unsupervised Bayesian classificati...
AbstractThe use of Bayesian Networks (BNs) as classifiers in different fields of application has rec...
Three Bayesian ideas are presented for supervised adaptive classifiers. First, it is argued that the...
International audienceRecently, several theoretical and applied studies have shown that unsupervised...
In this paper we present an average-case analysis of the Bayesian classifier, a simple induction alg...
In Classification learning, an algorithm is presented with a set of classified examples or ‘‘instanc...
The Naïve Bayesian Classifier and an Augmented Naïve Bayesian Classifier are applied to human classi...
The background and basic principle of Bayesian classification algorithm are briefly introduced at fi...
We employed a multilevel hierarchical Bayesian model in the task of exploiting relevant interactions...
Algorithms for learning classification trees have had successes in artificial intelligence and stati...
A criterion, based on Bayes' theorem, is described that defines the optimal set of classes (a classi...
The na ve Bayes classifier is built on the assumption of conditional independence between the attrib...
The task of inferring a set of classes and class descriptions most likely to explain a given data se...
In 1983 and 1984, the Infrared Astronomical Satellite (IRAS) detected 5,425 stellar objects and meas...
The naïve Bayes classifier is built on the assumption of conditional independence between the attrib...
Recently, several theoretical and applied studies have shown that unsupervised Bayesian classificati...
AbstractThe use of Bayesian Networks (BNs) as classifiers in different fields of application has rec...
Three Bayesian ideas are presented for supervised adaptive classifiers. First, it is argued that the...
International audienceRecently, several theoretical and applied studies have shown that unsupervised...
In this paper we present an average-case analysis of the Bayesian classifier, a simple induction alg...
In Classification learning, an algorithm is presented with a set of classified examples or ‘‘instanc...
The Naïve Bayesian Classifier and an Augmented Naïve Bayesian Classifier are applied to human classi...
The background and basic principle of Bayesian classification algorithm are briefly introduced at fi...
We employed a multilevel hierarchical Bayesian model in the task of exploiting relevant interactions...
Algorithms for learning classification trees have had successes in artificial intelligence and stati...
A criterion, based on Bayes' theorem, is described that defines the optimal set of classes (a classi...
The na ve Bayes classifier is built on the assumption of conditional independence between the attrib...