Sökning: "unsupervised classification"

Visar resultat 1 - 5 av 39 avhandlingar innehållade orden unsupervised classification.

1. 1. Molecular Classification of Bladder Cancer

   Författare :Gottfrid Sjödahl; Bröstcancer-genetik; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Bladder cancer; Subtype; Classification;

   Sammanfattning : 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. LÄS MER

3. 2. The EEG of the Neonatal Brain – Classification of Background Activity

   Författare :Johan Löfhede; Högskolan i Borås; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; hypoxia; newborn; segmentation; asphyxia; cerebral; classification; neonatal; EEG;

   Sammanfattning : 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. LÄS MER

4. 3. On Data Mining and Classification Using a Bayesian Confidence Propagation Neural Network

   Författare :Roland Orre; KTH; []
   Nyckelord :data mining; bcpnn; classification; neural network;

   Sammanfattning : 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. LÄS MER

5. 4. Deep learning for news topic identification in limited supervision and unsupervised settings

   Författare :Arezoo Hatefi; Frank Drewes; Johanna Björklund; Xuan-Son Vu; Eric Gaussier; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Topic Identification; Data Clustering; News Stream Clustering; Semi-Supervised Learning; Unsupervised Learning; Event Topics; News Stories; Multimodal News; Document Classification; Document Clustering; Deep Learning; Deep Clustering; Pre-trained Language Models;

   Sammanfattning : 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. LÄS MER

7. 5. Approximations of Bayes Classifiers for Statistical Learning of Clusters

   Författare :Magnus Ekdahl; Timo Koski; Jukka Corander; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Pattern Recognition; Stochastic Complexity; Naïve Bayes; Bayesian Network; Classification; Clustering; Chow-Liu trees; Mathematical statistics; Matematisk statistik;

   Sammanfattning : 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. LÄS MER