Sökning: "Klassificerare"

Visar resultat 1 - 5 av 162 uppsatser innehållade ordet Klassificerare.

  1. 1. Physical Exercise and Fatigue Detection using Machine Learning

    Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Filip Säterberg; Rasmus Nilsson; [2024]
    Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

    Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

  3. 2. The deductibles impact on the risk premium

    Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Ludvig Bergman; [2023]
    Nyckelord :deductible; insurance mathematics; non-life insurance pricing; Försäkringsmatematik; självrisk; självrisker;

    Sammanfattning : The aim of this master thesis is to derive methods that assesses the impact the deductiblehas on the risk premium of an insurance contract. The additive structure of a deductiblenecessitates approaches beyond treating it as a regular covariate in a generalized linearmodel for predicting the risk premium. LÄS MER

  4. 3. Double Machine Learning for Insurance Price Optimization

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Jakob Kristiansson; [2023]
    Nyckelord :DML; Double Machine Learning; Price Optimization; Insurance Pricing; DML; Dubbel Maskininlärning; Prisoptimering; Försäkringsprissättning;

    Sammanfattning : This thesis examines how recent advances in debaised machine learning can be used for estimating price elasticities of demand within the automotive insurance field. Traditional methods such as generalized linear model (GLM) to estimate demand has no way of ensuring there are no biases in the underlying data selection, especially when the confounding variables are many. LÄS MER

  5. 4. Predicting Myocardial Injury After Noncardiac Surgery

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

    Författare :Giordano Cauli; [2023]
    Nyckelord :Myocardial injury; hypotension; machine learning; non-cardiac surgery; F1; Myokardiell skada; hypotension; maskininlärning; icke-kardiell kirurgi; F1;

    Sammanfattning : Myocardial injury is the leading cause of death in Europe following non-cardiac surgery. Its causes, diagnosis, and treatment are still under investigation by the scientific community. Some research groups have hypothesized a connection between myocardial injury and hypotension during surgery. LÄS MER

  7. 5. Monthly heatwave prediction in Sweden based on Machine Learning techniques with remote sensing data

    Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknik

    Författare :Zhuoran Li; [2023]
    Nyckelord :Heatwave Prediction; Sweden; Machine Learning; Remote Sensing Data; Värmebölja förutsägelse; Sverige; Maskininlärning; Fjärravkänningsdata;

    Sammanfattning : Heatwave events as a kind of extreme climate event, have plagued the human race for the past few years. It severely influences people’s life quality, sometimes even leads to some serious diseases. In order to alleviate the possible damages heatwave events can do, some targeted actions are necessary and forecasting heatwaves is one of them. LÄS MER