Sökning: "naïve Bayes classifier"

Visar resultat 1 - 5 av 7 avhandlingar innehållade orden naïve Bayes classifier.

  1. 1. Approximations of Bayes Classifiers for Statistical Learning of Clusters

    Författare :Magnus Ekdahl; Timo Koski; Jukka Corander; Linköpings universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; 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

  2. 2. Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits

    Författare :Philip Tully; Anders Lansner; Matthias Hennig; Gordon Pipa; KTH; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Bayes rule; synaptic plasticity and memory modeling; intrinsic excitability; naïve Bayes classifier; spiking neural networks; Hebbian learning; neuromorphic engineering; reinforcement learning; temporal sequence learning; attractor network; Computer Science; Datalogi;

    Sammanfattning : 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. LÄS MER

  3. 3. Incremental Clustering of Source Code : a Machine Learning Approach

    Författare :Tobias Olsson; Morgan Ericsson; Sebastian Herold; Linnéuniversitetet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Naive Bayes; Source Code Clustering; Incremental Clustering; Software Architecture; Technical Debt; Computer Science; Datavetenskap;

    Sammanfattning : 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. LÄS MER

  4. 4. On approximations and computations in probabilistic classification and in learning of graphical models

    Författare :Magnus Ekdahl; Jose Antonio Lozano; Linköpings universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Mathematical statistics; factorizations; probabilistic classification; nodes; DNA strings; Mathematical statistics; Matematisk statistik;

    Sammanfattning : Model based probabilistic classification is heavily used in data mining and machine learning. For computational learning these models may need approximation steps however. LÄS MER

  5. 5. Classification models for high-dimensional data with sparsity patterns

    Författare :Annika Tillander; Tatjana Pavlenko; Daniel Thorburn; Patrik Ryden; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; High-dimensionality; supervised classification; classification accuracy; sparse; block-diagonal covariance structure; graphical Lasso; separation strength; discretization; Statistics; statistik;

    Sammanfattning : Today's high-throughput data collection devices, e.g. spectrometers and gene chips, create information in abundance. However, this poses serious statistical challenges, as the number of features is usually much larger than the number of observed units. LÄS MER