Search for dissertations about: "unsupervised classification"
Showing result 1 - 5 of 40 swedish dissertations containing the words unsupervised classification.
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1. Molecular Classification of Bladder Cancer
Abstract : Decisions in the treatment of bladder cancer today are based on clinical and pathological risk variables such as tumor stage and tumor grade. The importance of these conventional risk variables is well documented since more than 10 years, and they are used routinely in the clinics. READ MORE
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2. The EEG of the Neonatal Brain – Classification of Background Activity
Abstract : The brain requires a continuous supply of oxygen and nutrients, and even a short period of reduced oxygen supply can cause severe and lifelong consequences for the affected individual. The unborn baby is fairly robust, but there are of course limits also for these individuals. The most sensitive and most important organ is the brain. READ MORE
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3. On Data Mining and Classification Using a Bayesian Confidence Propagation Neural Network
Abstract : The aim of this thesis is to describe how a statisticallybased neural network technology, here named BCPNN (BayesianConfidence Propagation Neural Network), which may be identifiedby rewriting Bayes' rule, can be used within a fewapplications, data mining and classification with credibilityintervals as well as unsupervised pattern recognition.BCPNN is a neural network model somewhat reminding aboutBayesian decision trees which are often used within artificialintelligence systems. READ MORE
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4. Deep learning for news topic identification in limited supervision and unsupervised settings
Abstract : In today's world, following news is crucial for decision-making and staying informed. With the growing volume of daily news, automated processing is essential for timely insights and in aiding individuals and corporations in navigating the complexities of the information society. READ MORE
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5. Approximations of Bayes Classifiers for Statistical Learning of Clusters
Abstract : It is rarely possible to use an optimal classifier. Often the classifier used for a specific problem is an approximation of the optimal classifier. Methods are presented for evaluating the performance of an approximation in the model class of Bayesian Networks. READ MORE