Sökning: "permutation importance"

Visar resultat 1 - 5 av 20 uppsatser innehållade orden permutation importance.

  1. 1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Robert Iain Salter; [2023]
    Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

    Sammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER

  3. 2. Predicting Cryptocurrency Prices with Machine Learning Algorithms: A Comparative Analysis

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Harsha Nanda Gudavalli; Khetan Venkata Ratnam Kancherla; [2023]
    Nyckelord :Bitcoin; Cryptocurrency; Machine Learning;

    Sammanfattning : Background: Due to its decentralized nature and opportunity for substantial gains, cryptocurrency has become a popular investment opportunity. However, the highly unpredictable and volatile nature of the cryptocurrency market poses a challenge for investors looking to predict price movements and make profitable investments. LÄS MER

  4. 3. Bordtennis — Kopplingen mellan upplevda och fysiska egenskaper

    Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

    Författare :Molly Wörman; Ellen Waara Ankarstrand; [2023]
    Nyckelord :Maskininlärning Programmering SkLearn Bordtennis Frekvenssvar Modalanalys;

    Sammanfattning : I samarbete med STIGA Sports AB undersöker den här rapporten stommar hos bordtennisracketar och sambandet mellan den subjektiva upplevelsen av snabbhet och deras egenskaper. Undersökningen fokuserar på de fysiska egenskaperna, tjocklek och vikt, skillnaden i produktion, form, handtagssort, limsort och lack, samt uppmätta frekvenssvar. LÄS MER

  5. 4. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning

    Master-uppsats, KTH/Matematisk statistik

    Författare :Hannes Andersson; John Sjöberg; [2023]
    Nyckelord :Supply chain disruption; SMOTE; feature engineering; machine learning; random forest; statistics; applied mathematics; Störning i försörjningskedja; maskininlärning; matematik; statistik;

    Sammanfattning : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. LÄS MER

  7. 5. Estimating Brain Maturation in Very Preterm Neonates : An Explainable Machine Learning Approach

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Patrik Svensson; [2023]
    Nyckelord :Preterm Neonates; Brain Maturation; aEEG; Explainable Machine Learning; Feature Importance;

    Sammanfattning : Introduction: Assessing brain maturation in preterm neonates is essential for the health of the neonates. Machine learning methods have been introduced as a prospective assessment tool for neonatal electroencephalogram(EEG) signals. LÄS MER