Sökning: "stacked generalization"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden stacked generalization.

1. 1. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Ilya Ploshchik; [2023]
   Nyckelord :Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

   Sammanfattning : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. LÄS MER

3. 2. Control Aid Implementation -Modelling and simulation of triple extruder-

   Master-uppsats, Lunds universitet/Kemiteknik (CI)

   Författare :Karl Langsér; [2023]
   Nyckelord :Machine Learning; Extruder; Modelling; Simulation; Extreme learning machine; Chemical engineering; Technology and Engineering;

   Sammanfattning : In the production of their High Voltage Direct Current Cables (HVDC) and High Voltage Alternating Current Cables (HVAC), NKT uses triple extruders to create layers of insulation and semi-conduction. A model to predict the effect of extruder inputs on the cable’s insulation and semi-conducting layers has been created and trained to predict the extruder in discrete time. LÄS MER

4. 3. Data Augmentation to Improve Cross-Domain Generalization in Deep Learning MRI Segmentation

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Rasmus Helander; [2021]
   Nyckelord :deep learning; medical imaging; mri; segmentation; data augmentation; cyclegan; noisy labels; Mathematics and Statistics;

   Sammanfattning : Semantic segmentation of medical images is an important task with many applications. However, manually delineating 3D images is time-consuming and the demand for automation is high. For many image segmentation tasks, deep learning has provided state-of-the-art results. LÄS MER

5. 4. Using Ensemble Machine Learning Methods in Estimating Software Development Effort

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Alekhya Kanneganti; [2020]
   Nyckelord :Software Development Effort; Ensemble; Ensemble Learning; Stacking Ensemble; Software Development Effort Estimation; Machine Learning; Estimation of Software Development Effort; Effort Estimation;

   Sammanfattning : Background: Software Development Effort Estimation is a process that focuses on estimating the required effort to develop a software project with a minimal budget. Estimating effort includes interpretation of required manpower, resources, time and schedule. Project managers are responsible for estimating the required effort. LÄS MER

7. 5. An Ensemble Machine Learning Approach to Estimating Swiss Home Prices

   D-uppsats, Handelshögskolan i Stockholm/Institutionen för nationalekonomi

   Författare :Andreas Thuerlimann; [2018]
   Nyckelord :Machine Learning; Hedonic Pricing Model; Real Estate; Stacked Generalization;

   Sammanfattning : The price of a home is usually estimated by professional appraisers or by automated home valuation models, also known a hedonic pricing models. In the past, these models were largely based on linear regression models, however there is a trend towards using machine learning algorithms to estimate home prices. LÄS MER