Sökning: "Risk classification model"

Visar resultat 16 - 20 av 114 uppsatser innehållade orden Risk classification model.

1. 16. Prediction of Persistence to Treatment for Patients with Rheumatoid Arthritis using Deep Learning

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

   Författare :Serkan Arda Yilal; [2023]
   Nyckelord :Variational Autoencoders; Rheumatoid Arthritis; Precision Medicine; Treatment Prediction; Deep Learning; Supervised Learning; Rheumatoid Artrit; Precisionsmedicin; Behandlingsförutsägelse; Djupinlärning; Övervakat lärande;

   Sammanfattning : Rheumatoid Arthritis is an inflammatory joint disease that is one of the most common autoimmune diseases in the world. The treatment usually starts with a first-line treatment called Methotrexate, but it is often insufficient. One of the most common second-line treatments is Tumor Necrosis Factor inhibitors (TNFi). LÄS MER

3. 17. Straight to the Heart : Classification of Multi-Channel ECG-signals using MiniROCKET

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

   Författare :Stefan Christiansson; [2023]
   Nyckelord :MiniROCKET; Time-series analysis; Multi-variate; Classification; Convolutional Neural Network; MiniROCKET; Tidsserieanalys; Multivariat; Klassifikation; Convolutional Neural Network;

   Sammanfattning : Machine Learning (ML) has revolutionized various domains, with biomedicine standing out as a major beneficiary. In the realm of biomedicine, Convolutional Neural Networks (CNNs) have notably played a pivotal role since their inception, particularly in applications such as time-series classification. LÄS MER

4. 18. Applying the Shadow Rating Approach: A Practical Review

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Viktor Barry; Carl Stenfelt; [2023]
   Nyckelord :Shadow Rating; probability of default; low default portfolio; credit risk; statistical learning; financial regulation; Basel; Pluto and Tasche; Skuggrating; sannolikhet av fallissemang; lågfallissemangsportfölj; kreditrisk; statistisk inlärning; finansiella regelverk; Basel; Pluto och Tasche;

   Sammanfattning : The combination of regulatory pressure and rare but impactful defaults together comprise the domain of low default portfolios, which is a central and complex topic that lacks clear industry standards. A novel approach that utilizes external data to create a Shadow Rating model has been proposed by Ulrich Erlenmaier. LÄS MER

5. 19. Machine Learning to predict student performance based on well-being data : a technical and ethical discussion

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

   Författare :Lucy McCarren; [2023]
   Nyckelord :Machine Learning; Data Science; Learning Analytics; Maskininlärning; Data Science; Inlärningsanalys;

   Sammanfattning : The data provided by educational platforms and digital tools offers new ways of analysing students’ learning strategies. One such digital tool is the wellbeing platform created by EdAider, which consists of an interface where students can answer questions about their well-being, and a dashboard where teachers and schools can see insights into the well-being of individual students and groups of students. LÄS MER

7. 20. Investigating the Performance of Random Forest Classification for Stock Trading

   Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

   Författare :Oscar Nordfjell; Gustav Ring; [2023]
   Nyckelord :Random Forest; Random Forest Classification; Stock Trading; Trading Strategy;

   Sammanfattning : We show that with the implementation presented in this paper, the Random Forest Classification model was able to predict whether or not a stock was going to increase in value during the coming day with an accuracy higher than 50\% for all stocks included in this study. Furthermore, we show that the active trading strategy presented in this paper generated higher returns and higher risk-adjusted returns than the passive investment in the stocks underlying the strategy. LÄS MER