Sökning: "feature selection"
Visar resultat 21 - 25 av 318 uppsatser innehållade orden feature selection.
21. Exploring Feature Selection Techniques for Machine Learning-based Melanoma Skin Cancer Classification
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : One of the most globally common types of cancer is skin cancer, where melanoma is the most deadly form. An important and promising tool for diagnosing diseases such as skin cancer is computer aided diagnostics, a tool which utilizes machine learning to predict and classify cancer. LÄS MER
22. A comparative study on anapproach to print Industrial Toolsvia Additive Manufacturing for Volume Production from Technical, Economic, and Environmental aspects
Master-uppsats, KTH/ProduktionsutvecklingSammanfattning : The thesis explores a path to use Additive Manufacturing as an approach for volume production of Industrial Technique Business Area Tools, addressing the challenges of manufacturing complexity, low volume demand, and quality control for both Atlas Copco Industrial Technique industrial tools (Tool 1 & Tool 2). This study is done in cooperation with Atlas Copco Industrial Technique, comparing the technological, economic, and environmental performance of AM versus the current manufacturing approach from a round bar. LÄS MER
23. Regularizing Vision-Transformers Using Gumbel-Softmax Distributions on Echocardiography Data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis introduces an novel approach to model regularization in Vision Transformers (ViTs), a category of deep learning models. It employs stochastic embedded feature selection within the context of echocardiography video analysis, specifically focusing on the EchoNet-Dynamic dataset. LÄS MER
24. Explainable Machine Learning in Cardiovascular Diagnostics
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. LÄS MER
25. Determining Important Features for Melanoma Classification Through Feature Selection
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Skin cancer is a common disease and malignant melanoma is the most dangerous form of it. Although dangerous, the survival rate of melanoma patients is high if the diagnosis is made at an early stage. Computer aided diagnostics has been shown to have potential in accurately diagnosing the disease utilizing machine learning. LÄS MER