Sökning: "interpretable model"
Visar resultat 1 - 5 av 61 uppsatser innehållade orden interpretable model.
1. Classifying Previous Covid-19 Infection : Advanced Logistic Regression Approach
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : The study aimed to developed a logistic model based on antibody proteins, vaccinations and demographic factors that predicts previous infection in Covid-19. The data set comprised of 2750 individuals from eldercare homes in Sweden, with four test dates executed between October of 2021 and August of 2022. LÄS MER
2. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER
3. Real-time Energy Performance Tracking
Master-uppsats, Högskolan i Skövde/Institutionen för informationsteknologiSammanfattning : Energy performance tracking is becoming increasingly significant in the building industry as a means of improving energy efficiency. This thesis provides answers to the questions related to improving energy tracking system in general, including its potentials, problems and challenges. LÄS MER
4. Increasing explainability of neural network based retail credit risk models
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Due to their ’black box’ nature, Artificial Neural Networks (ANN) are not permitted for use in various applications. One such application is mortgage credit risk modeling. LÄS MER
5. Aggregating predictions of a yeast semantic segmentation model : Reducing a pixel classifier into a binary image classifier
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The introduction of machine learning in clinical microbiology is important for aiding clinical laboratories with highly repetitive tasks that are fatiguing, error-prone, and require long employee training time due to the complex nature of the task. A challenging task that belongs to the subareas that need assistance is yeast detection in fluorescence microscopy where various yeast morphologies exist. LÄS MER