Search for dissertations about: "Ensemble Learning"

Showing result 1 - 5 of 32 swedish dissertations containing the words Ensemble Learning.

  2. 1. Utilizing Diversity and Performance Measures for Ensemble Creation

    Author : Tuve Löfström; Högskolan i Skövde; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; Ensemble Learning; Machine Learning; Diversity; Artificial Neural Networks; Data Mining; Information Fusion; Computer science; Datavetenskap; Teknik; Technology; ensemble learning; machine learning; diversity; artificial neural networks; information fusion; Computer Science; data mining;

    Abstract : An ensemble is a composite model, aggregating multiple base models into one predictive model. An ensemble prediction, consequently, is a function of all included base models. Both theory and a wealth of empirical studies have established that ensembles are generally more accurate than single predictive models. READ MORE

  4. 2. Designing for Adaptable Learning

    Author : Amir Haj-Bolouri; Lars Svensson; Thomas Winman; Per Flensburg; Högskolan Väst; []
    Keywords : SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Design; action design research; design science research; information systems; integration work; civic orientation; work-integrated learning; e-learning; adaptable learning; Work Integrated Learning; Arbetsintegrerat lärande; Informatik; Informatics;

    Abstract : The research in this thesis emphasizes the endeavor of designing for adaptable learning. Designing for adaptable learning is understood as an overall response to designing for integration work. Designing for integration work is thus classified as a special case of designing for adaptable learning. READ MORE

  5. 3. Improving diagnosis of acute coronary syndromes in an emergency setting: A machine learning approach

    Author : Michael Green; Beräkningsbiologi och biologisk fysik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; ensemble; artificial neural network; machine learning; acute coronary syndrome; electrocardiogram; case based explanation; decision support system;

    Abstract : Acute coronary syndrome (ACS) is the biggest people killer in the western world today. Despite well trained physicians and reliable diagnostic tools, diagnosing ACS early in the emergency departments (ED) remains a challenge. READ MORE

  6. 4. Modeling Music : Studies of Music Transcription, Music Perception and Music Production

    Author : Anders Elowsson; Anders Friberg; Pawel Herman; Anders Askenfelt; Gerhard Widmer; KTH; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Music Information Retrieval; MIR; Music; Music Transcription; Music Perception; Music Production; Tempo Estimation; Beat Tracking; Polyphonic Pitch Tracking; Polyphonic Transcription; Music Speed; Music Dynamics; Long-time average spectrum; LTAS; Algorithmic Composition; Deep Layered Learning; Convolutional Neural Networks; Rhythm Tracking; Ensemble Learning; Perceptual Features; Representation Learning;

    Abstract : This dissertation presents ten studies focusing on three important subfields of music information retrieval (MIR): music transcription (Part A), music perception (Part B), and music production (Part C).In Part A, systems capable of transcribing rhythm and polyphonic pitch are described. READ MORE

  7. 5. Artificial intelligence in weather and climate prediction : Learning atmospheric dynamics

    Author : Sebastian Scher; Gabriele Messori; Roberto Buizza; Stockholms universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Atmospheric Sciences and Oceanography; atmosfärvetenskap och oceanografi;

    Abstract : Weather and climate prediction is dominated by high dimensionality, interactions on many different spatial and temporal scales and chaotic dynamics. This makes many problems in the field quite complex ones, and also state-of-the-art numerical models are - despite their immense computational costs - not sufficient for many applications. READ MORE