Sökning: "maskininlärning regression"

Visar resultat 16 - 20 av 269 uppsatser innehållade orden maskininlärning regression.

  1. 16. 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

  3. 17. Inferring Gene regulatory networks using Graph Neural Networks

    Master-uppsats, KTH/Genteknologi

    Författare :Sohta Makino; [2023]
    Nyckelord :Graph Attention Network; Gene regulatory Network; Transcription; Data Science; Machine learning; Genreglering; transkription; dataanalys; Inferens; maskininlärning;

    Sammanfattning : Inom beräkningsbiologin är det snabbt på väg att bli allt vanligare att ta fram genetiska regleringsnätverk (GRN). På grund av storleken på de undersökta nätverken använder många forskare maskininlärning för att härleda GRN från genuttrycksdata, vanligtvis från RNA-seq. LÄS MER

  4. 18. Explainable Machine Learning in Cardiovascular Diagnostics

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

    Författare :Alexander Gutell; Ludvig Skare; [2023]
    Nyckelord :;

    Sammanfattning : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. LÄS MER

  5. 19. Predicting Short-term Absences of a Railway Crew using Historical Data

    Master-uppsats, KTH/Matematisk statistik

    Författare :Agnes Björnfot; Sandra Fjelkestam; [2023]
    Nyckelord :statistics; machine learning; absence prediction; random forest; XGBoost; quantile regression; statistik; maskininlärning; frånvaroprognoser; random forest; XGBoost; kvantilregression;

    Sammanfattning : Transportation via train is considered the most environmentally friendly way of traveling and is widely seen as the future of transportation. Canceled and delayed trains worsen customer satisfaction; thus, punctual trains are crucial for railway companies. LÄS MER

  7. 20. Joinpoint regression analysis of the COVID-19 epidemic curve in Sweden : A descriptive trend analysis of the different regions in Sweden

    Kandidat-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Sebastian Bergwall; Duc Tran; [2023]
    Nyckelord :COVID-19; time series; descriptive analysis; grid search; joinpoint regression;

    Sammanfattning : Since the beginning of the global outbreak, the Swedish Public Health Agency has been closely monitoring the situation regarding COVID-19. Understanding and mapping the behaviour of the COVID-19 epidemic curve in Sweden is of great interest and conducting a descriptive analysis may yield additional important insights. LÄS MER