Sökning: "Prediction interval"

Visar resultat 1 - 5 av 69 uppsatser innehållade orden Prediction interval.

1. 1. Uncertainty Estimation in Radiation Dose Prediction U-Net

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Frida Skarf; [2023]
   Nyckelord :Radiation dose prediction models; U-net; quantile regression; Monte Carlo Dropout; epistemic uncertainty estimation; aleatoric uncertainty estimation; Stråldospredicerande modeller; U-net; kvantilregression; Monte Carlo Dropout; epistemisk osäkerhetsskattning; aletorisk osäkerhetsskattning;

   Sammanfattning : The ability to quantify uncertainties associated with neural network predictions is crucial when they are relied upon in decision-making processes, especially in safety-critical applications like radiation therapy. In this paper, a single-model estimator of both epistemic and aleatoric uncertainties in a regression 3D U-net used for radiation dose prediction is presented. LÄS MER

3. 2. MODELING INPUT VARIABLE AGE IN SEPSIS PREDICTION USING TREE-BASED MODELS

   Master-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Oscar Wastesson; [2023]
   Nyckelord :Machine learning; decision trees; sepsis; classification;

   Sammanfattning : Last observation carried forward (LOCF) is a common imputation method, regularly used for clinical data. It is based on the principle that the most recent observation that is known is carried forward to replace missing values. LÄS MER

4. 3. Calculating Value-at-Risk under the G-Normal distribution. : Applied with Swedish data.

   Kandidat-uppsats, Uppsala universitet/Nationalekonomiska institutionen

   Författare :Daniel Renvall Moberg; [2023]
   Nyckelord :;

   Sammanfattning : Value–at–Risk (VaR) since its birth at JPMorgan in the 1990s, has become widely adopted by first and foremost the financial industry, but in later days regulatory authorities as a way of calculating downside risk. The subject in hand has led to numerous attempts by both the industry as well as scholars to find the perfect settings to calculate VaR. LÄS MER

5. 4. Modeling and quantifying uncertainty in bus arrival timeprediction

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Olof Josefsson; [2023]
   Nyckelord :uncertainty quantification; arrival time prediction;

   Sammanfattning : Public transportation operates in an environment which, due to its nature of numerous possibly influencing factors, is highly stochastic. This makes predictions of arrival times difficult, yet it’s important to be accurate in order to adhere to travelers expectations. LÄS MER

7. 5. Predicting Customer Churn in E-commerce Using Statistical Modeling and Feature Importance Analysis : A Comparison of Random Forest and Logistic Regression Approaches

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Amanda Rudälv; [2023]
   Nyckelord :Customer behavior; E-commerce; Churn prediction; Statistical model; Machine learning; Random forest; Logistic regression; Feature importance; Kundbeteende; E-handel; Kundbortfall; Statistisk modell; Maskininlärning; Random forest; Logistisk regression; Variabelsignifikans;

   Sammanfattning : While operating in online markets offers opportunities for expanded assortment and convenience, it also poses challenges such as increased competition and the need to build personal relationships with customers. Customer retention be- comes crucial in maintaining a successful business, emphasizing the importance of understanding customer behavior. LÄS MER