Essays about: "Gaussian Process regression"
Showing result 21 - 25 of 60 essays containing the words Gaussian Process regression.
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21. Constrained Gaussian Process Regression Applied to the Swaption Cube
University essay from KTH/Matematik (Avd.)Abstract : This document is a Master Thesis report in financial mathematics for KTH. This Master thesis is the product of an internship conducted at Nexialog Consulting, in Paris. This document is about the innovative use of Constrained Gaussian process regression in order to build an arbitrage free swaption cube. READ MORE
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22. Data-Driven Engine Fault Classification and Severity Estimation Using Interpolated Fault Modes from Limited Training Data
University essay from Linköpings universitet/FordonssystemAbstract : Today modern vehicles are expected to be safe, environmentally friendly, durable and economical. Monitoring the health of the vehicle is therefore more important than ever. As the complexity of vehicular systems increases the need for efficient monitoring methods has increased as well. READ MORE
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23. Evaluating the suitability of Gaussian process regression and XGBoost on electricity price forcasting
University essay from Lunds universitet/Matematisk statistikAbstract : Electricity finds itself different from other fresh-ware commodities, it cannot easily be stored. This characteristic trait of electricity results in traditional pricing methods not working for electricity pricing. Thus different pricing schemes are needed, such as Price Forward Curves (PFC) or pricing against a price level. READ MORE
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24. Machine Unlearning and hyperparameters optimization in Gaussian Process regression
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The establishment of the General Data Protection Regulation (GDPR) in Europe in 2018, including the "Right to be Forgotten" poses important questions about the necessity of efficient data deletion techniques for trained Machine Learning models to completely enforce this right, since retraining from scratch such models whenever a data point must be deleted seems impractical. We tackle such a problem for Gaussian Process Regression and define in this paper an efficient exact unlearning technique for Gaussian Process Regression which completely include the optimization of the hyperparameters of the kernel function. READ MORE
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25. Phase-Out Demand Forecasting : Predictive modeling on forecasting product life cycle
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The phase-out stage in a product life cycle can face unpredictable demand. Accurate forecast of the phase-out demand can help supply chain managers to control the number of obsolete inventories. Consequently, having a positive effect in terms of resources and lower scrap costs. READ MORE
