Sökning: "Ensemblemetoder"

Hittade 5 uppsatser innehållade ordet Ensemblemetoder.

  1. 1. Comparing Ensemble Methods with Individual Classifiers in Machine Learning for Diabetes Detection

    Kandidat-uppsats, KTH/Datavetenskap

    Författare :Samuel Härner; David Ekman; [2022]
    Nyckelord :;

    Sammanfattning : Diabetes is a common disease that is characterized by several health markers. These markers can be used in machine learning to help predict the presence of diabetes in an individual. LÄS MER

  3. 2. Pricing collateralized loan obligation tranches using machine learning : Machine learning applied to financial data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Marcus Enström; [2022]
    Nyckelord :Collateralized loan obligation; Machine learning; Artificial neural networks; Financial data; Ensemble methods; Collateralized loan obligation; Maskininlärning; Artificiella neurala nätverk; Finansiell data; Ensemblemetoder;

    Sammanfattning : Machine learning and neural networks have recently become very popular in a large category of domains, partly thanks to their ability to solve complex problems by finding patterns in data, but also due to an increase in computing power and data availability. Successful applications of machine learning include for example image classification, natural language processing, and product recommendation. LÄS MER

  4. 3. Uncertainty Estimation for Deep Learning-based LPI Radar Classification : A Comparative Study of Bayesian Neural Networks and Deep Ensembles

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Måns Ekelund; [2021]
    Nyckelord :LPI radar; Uncertainty Quantification; Deep Learning; Bayesian Neural Networks; Deep Ensembles; LPI radar; Osäkerhetsskattning; Djupinlärning; Bayesianska neurala nätverk; Djupa ensembler;

    Sammanfattning : Deep Neural Networks (DNNs) have shown promising results in classifying known Low-probability-of-intercept (LPI) radar signals in noisy environments. However, regular DNNs produce low-quality confidence and uncertainty estimates, making them unreliable, which inhibit deployment in real-world settings. LÄS MER

  5. 4. Classification in Functional Data Analysis : Applications on Motion Data

    Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Viktor Kröger; [2021]
    Nyckelord :Classification; Functional Data Analysis; FDA; motion data; ligament injury;

    Sammanfattning : Anterior cruciate knee ligament injuries are common and well known, especially amongst athletes.These injuries often require surgeries and long rehabilitation programs, and can lead to functionloss and re-injuries (Marshall et al., 1977). LÄS MER

  7. 5. Hybrid Ensemble Methods: Interpretible Machine Learning for High Risk Aeras

    Master-uppsats, KTH/Matematisk statistik

    Författare :Maria Ulvklo; [2021]
    Nyckelord :Interpretability; Machine Learning; Sparse Data; Ensemble; Cyber Security; High Risk Sectors; Tolkbarhet; Maskininlärning; Gles Data; Ensemblemetoder; Cybersäkerhet; Högriskområden;

    Sammanfattning : Despite the access to enormous amounts of data, there is a holdback in the usage of machine learning in the Cyber Security field due to the lack of interpretability of ”Black­box” models and due to heterogenerous data. This project presents a method that provide insights in the decision making process in Cyber Security classification. LÄS MER