Sökning: "Ensemble Learning"

Visar resultat 1 - 5 av 41 avhandlingar innehållade orden Ensemble Learning.

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

    Författare :Tuve Löfström; Högskolan i Skövde; []
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  2. 2. Designing for Adaptable Learning

    Författare :Amir Haj-Bolouri; Lars Svensson; Thomas Winman; Per Flensburg; Högskolan Väst; []
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  3. 3. Svängrum : för en kreativ musikpedagogik

    Författare :Anna Linge; Malmö högskola; []
    Nyckelord :HUMANITIES; HUMANIORA; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SAMHÄLLSVETENSKAP; HUMANIORA; SOCIAL SCIENCES; HUMANITIES; music education; authentic learning; transformative learning; motivation; creative music education; new rules; Svängrum; Humanities; Social Sciences; Music Education; Musikpedagogik; tranformative learning; music education; authentic learning; transformative leaming;

    Sammanfattning : The purpose of this doctoral dissertation is to investigate what mechanisms produce a creative music education. The method used is based on critical realism where a social science phenomenon consists of empirica!events, operating mechanisms and the structures that produce them. LÄS MER

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

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

    Sammanfattning : 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. LÄS MER

  5. 5. Modeling Music : Studies of Music Transcription, Music Perception and Music Production

    Författare :Anders Elowsson; Anders Friberg; Pawel Herman; Anders Askenfelt; Gerhard Widmer; KTH; []
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER