Sökning: "Generalized linear model GLM"
Visar resultat 1 - 5 av 18 uppsatser innehållade orden Generalized linear model GLM.
1. Double Machine Learning for Insurance Price Optimization
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)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
2. Using Gradient Boosting to Identify Pricing Errors in GLM-Based Tariffs for Non-life Insurance
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Most non-life insurers and many creditors use regressions, more specifically Generalized Linear Models (GLM), to price their liabilities. One limitation with GLMs is that interactions between predictors are handled manually, which makes finding interactions a tedious and time-consuming task. LÄS MER
3. Spridningsfaktorer av invasiva arter inom C-verksamheter
Kandidat-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : Den tilltagande höga nivån av urbanisering och vägbyggen är en bidragande faktor till spridning av invasiva arter. Transporter och frekventa vegetationsstörningar resulterar i homogena, öppna och soliga landskap med minskad konkurrens där snabbt växande ruderala arter med hög ihållande fröproduktion etablerar sig, varav många är invasiva. LÄS MER
4. Technical Support and Self-Service Troubleshooting: An Insurance Approach
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Technical support and services are growing more and more competitive and have become a selling point for many companies. One way companies differentiate themselves is through extensive self-service solutions as a part of the support structure. However, the underlying cost drivers are not well understood. LÄS MER
5. Supervised Learning for Prediction of Tumour Mutational Burden
Master-uppsats, KTH/Matematisk statistikSammanfattning : Tumour Mutational Burden is a promising biomarker to predict response to immunotherapy. In this thesis, statistical methods of supervised learning were used to predict TMB: GLM, Decision Trees and SVM. LÄS MER