Sökning: "Probabilistic Machine Learning"

Visar resultat 1 - 5 av 50 uppsatser innehållade orden Probabilistic Machine Learning.

1. 1. Modeling Stoppage Time as a Convolution of Negative Binomials

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

   Författare :Råvan Talani; [2023]
   Nyckelord :Machine learning; negative binomial; convolution; stoppage time; injury time; extra time; football;

   Sammanfattning : This thesis develops and evaluates a probabilistic model that estimates the stoppage time in football. Stoppage time represents the additional minutes of play given after the original matchtime is over. It is crucial in determining the course of events during the remainder of a match, thereby affecting the odds of live sports betting. LÄS MER

3. 2. Evaluating the Effect of Meta-Labeling on Equity Market Neutral Strategy

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Niclas Wölner-Hanssen; [2023]
   Nyckelord :Meta-Labeling; Probabilistic Sharpe Ratio; Equity Market Neutral; Mathematics and Statistics;

   Sammanfattning : This thesis aims to construct an Equity Market Neutral (EMN) strategy framework to predict intraday excess returns of stocks within the S&P 500 index by utilizing machine learning techniques proposed by (López de Prado, 2018). The constructed EMN strategies within the framework utilizes techniques such as Stacked Single Feature Importance (SSFI), sample weighting, Probabilistic Sharpe Ratio (PSR), and meta-labeling. LÄS MER

4. 3. Clinical Assessment of Deep Learning-Based Uncertainty Maps in Lung Cancer Segmentation

   Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Författare :Federica Carmen Maruccio; [2023]
   Nyckelord :3D U-Net; Contouring; Clinical validation; Deep learning; Lung cancer; Monte Carlo dropout; Probability map; Reliability diagram; Segmentation; Uncertainty map;

   Sammanfattning : Prior to radiation therapy planning, tumours and organs at risk need to be delineated. In recent years, deep learning models have opened the possibility of automating the contouring process, speeding up the procedures and helping clinicians. LÄS MER

5. 4. Generation of Synthetic Traffic Sign Images using Diffusion Models

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Johanna Carlson; Lovisa Byman; [2023]
   Nyckelord :Machine Learning; Computer Vision; Diffusion Models; Traffic Sign Recognition; Traffic Sign Classification; Synthetic Data; Maskininlärning; Datorseende; Diffusionsmodeller; Trafikskyltsigenkänning; Trafikskyltsklassificering; Syntetisk data;

   Sammanfattning : In the area of Traffic Sign Recognition (TSR), deep learning models are trained to detect and classify images of traffic signs. The amount of data available to train these models is often limited, and collecting more data is time-consuming and expensive. LÄS MER

7. 5. Conform with the Wind : Processing short-term ensemble forecasts with conformal based methods for probabilistic wind-speed forecasting

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Simon Althoff; [2023]
   Nyckelord :wind-speed; probabilistic; forecasts; forecasting; ensemble; post-processing; conformal prediction; conformal predictive systems; quantile regression forest; non-exchangeable; Mathematics and Statistics;

   Sammanfattning : Forecasting wind has always been an interesting subject, and as large parts of the world are relying more on wind for power production it is becoming even more important to have reliable forecasts. Probabilistic forecasts, where distributions are predicted in contrast to deterministic forecasts, are impor- tant for informed decision making. LÄS MER