Search for dissertations about: "naive"
Showing result 1 - 5 of 378 swedish dissertations containing the word naive.
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1. A naïve sampling model of intuitive confidence intervals
Abstract : A particular field in research on judgment and decision making (JDM) is concerned with realism of confidence in one’s knowledge. An interesting finding is the so-called format dependence effect, which implies that assessment of the same probability distribution generates different conclusions about over- or underconfidence depending on the assessment format. READ MORE
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2. 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
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3. Incremental Clustering of Source Code : a Machine Learning Approach
Abstract : Technical debt at the architectural level is a severe threat to software development projects. Uncontrolled technical debt that is allowed to accumulate will undoubtedly hinder speedy development and maintenance, introduce bugs and problems in the software product, and may ultimately result in the abandonment of the source code. READ MORE
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4. Overconfidence and Format Dependence in Subjective Probability Intervals: Naive Estimation and Constrained Sampling
Abstract : A particular field in research on judgment and decision making (JDM) is concerned with realism of confidence in one’s knowledge. An interesting finding is the so-called format dependence effect which implies that assessment of the same probability distribution generates different conclusions about over- or underconfidence bias depending on the assessment format. READ MORE
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5. Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits
Abstract : Cortical and subcortical microcircuits are continuously modified throughout life. Despite ongoing changes these networks stubbornly maintain their functions, which persist although destabilizing synaptic and nonsynaptic mechanisms should ostensibly propel them towards runaway excitation or quiescence. READ MORE