Sökning: "Ensemble Learning"
Visar resultat 1 - 5 av 33 avhandlingar innehållade orden Ensemble Learning.
- Detta är en avhandling från Örebro universitet
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
- Detta är en avhandling från Trollhättan : University West
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. Improving diagnosis of acute coronary syndromes in an emergency setting: A machine learning approachDetta är en avhandling från Trollhättan : University West
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
- Detta är en avhandling från Stockholm : KTH Royal Institute of Technology
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
- Detta är en avhandling från Department of Computer Science, Lund University
Sammanfattning : The human brain can be seen as an ensemble of interconnected neurons, more or less specialized to solve different cognitive and motor tasks. In computer science, the term deep learning is often applied to signify sets of interconnected nodes, where deep means that they have several computational layers. LÄS MER