Sökning: "maskininlärning regression"
Visar resultat 1 - 5 av 128 uppsatser innehållade orden maskininlärning regression.
Sammanfattning : This study examines whether machine learning techniques such as neural networks contain predictability when modeling asset prices and if they can improve on asset pricing prediction compared to traditional OLS-regressions. This is analyzed through measuring and comparing the out-of-sample R2 to find each models’ predictive power. LÄS MER
- Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS); KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The purpose of this article is to evaluate the impact a supervised machine learning classification model can have on the process of internal customer support within a large digitized company. Chatbots are becoming a frequently used utility among digital services, though the true general impact is not always clear. LÄS MER
3. Tillämpning av maskininlärning för att införa automatisk adaptiv uppvärmning genom en studie på KTH Live-In Labs lägenheterKandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumption through adaptive heating that uses climate data to detect occupancy in apartments using machine learning. The application of the study has been made using environmental data from one of KTH Live-In Labs apartments. LÄS MER
- Master-uppsats, KTH/Matematisk statistik
Sammanfattning : Product similarity matching for food retail is studied in this thesis. The goal is to find products that are similar but not necessarily of the same brand which can be used as a replacement product for a product that is out of stock or does not exist in a specific store. LÄS MER
5. A Deep Learning Approach to Predicting the Length of Stay of Newborns in the Neonatal Intensive Care UnitMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Recent advancements in machine learning and the widespread adoption of electronic healthrecords have enabled breakthroughs for several predictive modelling tasks in health care. One such task that has seen considerable improvements brought by deep neural networks is length of stay (LOS) prediction, in which research has mainly focused on adult patients in the intensive care unit. LÄS MER