Essays about: "Regressionsträd"

Found 4 essays containing the word Regressionsträd.

  1. 1. Applying the Shadow Rating Approach: A Practical Review

    University essay from KTH/Matematik (Avd.)

    Author : Viktor Barry; Carl Stenfelt; [2023]
    Keywords : Shadow Rating; probability of default; low default portfolio; credit risk; statistical learning; financial regulation; Basel; Pluto and Tasche; Skuggrating; sannolikhet av fallissemang; lågfallissemangsportfölj; kreditrisk; statistisk inlärning; finansiella regelverk; Basel; Pluto och Tasche;

    Abstract : The combination of regulatory pressure and rare but impactful defaults together comprise the domain of low default portfolios, which is a central and complex topic that lacks clear industry standards. A novel approach that utilizes external data to create a Shadow Rating model has been proposed by Ulrich Erlenmaier. READ MORE

  3. 2. Estimating the load weight of freight trains using machine learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Erik Kongpachith; [2023]
    Keywords : Railway freight Transport; Rail Vehicle Weighing; Y25 Bogie; Sdggmrss T3000eD; GENSYS; Machine Learning; Regression; Polynomial Regression; Regression Trees; Random Forest Regression; Support Vector Regression; Järnvägsgods transport; Vägning av järnvägsfordon; Y25 Bogie; Sdggmrss T3000eD; GENSYS; Maskininlärning; Regression; Polynom Regression; Regressionsträd; Random Forest Regression; Support Vector Regression;

    Abstract : Accurate estimation of the load weight of freight trains is crucial for ensuring safe, efficient and sustainable rail freight transports. Traditional methods for estimating load weight often suffer from limitations in accuracy and efficiency. READ MORE

  4. 3. Using Gradient Boosting to Identify Pricing Errors in GLM-Based Tariffs for Non-life Insurance

    University essay from KTH/Matematik (Avd.)

    Author : Felix Greberg; Andreas Rylander; [2022]
    Keywords : GLM; Gradient Boosting; XGBoost; Non-life insurance; Property Casualty; Rate making; Insurance Tariff; MTPL insurance; Machine learning; Regression trees; Tweedie regression; Credit risk; GLM; Gradient Boosting; XGBoost; Skadeförsäkring; Prissättning; Försäkringstariff; Trafikförsäkring; Regressionsträd; Maskininlärning; Tweedie-regression; Kreditrisk;

    Abstract : 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. READ MORE

  5. 4. Simulation and time-series analysis for Autonomous Emergency Braking systems

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Zhiying Xu; [2021]
    Keywords : Autonomous Driving AD ; CARLA; Autonomous Emergency Braking AEB ; Deep Learning; Time-series analysis; Autonom körning; CARLA; Autonomt nödsystem; Djup lärning; Tidsföljder;

    Abstract : One central challenge for Autonomous Driving (AD) systems is ensuring functional safety. This is affected by all parts of vehicle automation systems: environment perception, decision making, and actuation. READ MORE