Essays about: "double machine learning"
Showing result 1 - 5 of 33 essays containing the words double machine learning.
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1. Double Machine Learning for Insurance Price Optimization
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : 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. READ MORE
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2. Machine Learning for Pulse Shape Analysis of Heavy Ions
University essay from Uppsala universitet/Tillämpad kärnfysikAbstract : Most of the Generation IV nuclear reactors designs are intended to operate with a fast neutron spectrum. This necessitates further investigation into nuclear fuel behaviour because fast neutrons yield a higher neutron multiplicity with fission fragments, significantly impacting the criticality assessment of these reactors. READ MORE
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3. The Impact of Parental Education on the Early Detection of Autism Spectrum Disorder in Children.
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : Utilizing the Double Machine Learning (DML) framework with both Partially Linear Regression (PLR) and Interactive Regression Models (IRM), this study examined the crucial role of parental education in the early detection of Autism Spectrum Disorder (ASD). Analysis was conducted on comprehensive data from the National Survey of Children's Health spanning the years 2017 to 2021. READ MORE
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4. A Causal Analysis of Cat Bond Markets
University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomiAbstract : This work is a contribution to the causal analysis of the catastrophe bond market, which has generated high excess returns over the last two decades. Since these excess returns remain partially unexplainable and the interest in catastrophe bonds is increasing, the causal study of the factors affecting their premiums is of high relevance. READ MORE
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5. Mobile Traffic Classification and Multi-Cell Base Station Control for Energy-Efficient 5G Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The global energy consumption of mobile networks is rapidly increasing due to the exponential growth of mobile network traffic. The advent of next-generation cellular technologies such as fifth-generation (5G) and beyond promises higher network throughput and lower latency but also demands higher power consumption for its denser base station (BS) deployment and more energy-intensive processors. READ MORE