Essays about: "Supervised learning by classification"
Showing result 16 - 20 of 170 essays containing the words Supervised learning by classification.
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16. ML enhanced interpretation of failed test result
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This master thesis addresses the problem of classifying test failures in Ericsson AB’s BAIT test framework, specifically distinguishing between environment faults and product faults. The project aims to automate the initial defect classification process, reducing manual work and facilitating faster debugging. READ MORE
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17. Semi-supervised anomaly detection in mask writer servo logs : An investigation of semi-supervised deep learning approaches for anomaly detection in servo logs of photomask writers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Semi-supervised anomaly detection is the setting, where in addition to a set of nominal samples, predominantly normal, a small set of labeled anomalies is available at training. In contrast to supervised defect classification, these methods do not learn the anomaly class directly and should have better generalization capability as new kinds of anomalies are introduced at test time. READ MORE
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18. Parliament proceeding classification via Machine Learning algorithms: A case of Greek parliament proceedings
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : The Greek Parliament is a critical institution for the Greek Democracy, where important decisions are made that affect the lives of millions of people. It consists of representatives from different political parties, and each party has a unique political ideology, stance, and agenda. READ MORE
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19. Data-Driven Traffic Forecasting for Completed Vehicle Simulation: : A Case Study with Volvo Test Trucks
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : This thesis offers a thorough investigation into the application of machine learning algorithms for predicting the presence of vehicles in a traffic setting. The research primarily focuses on enhancing vehicle simulation by employing data-driven traffic prediction methods. The study approaches the problem as a binary classification task. READ MORE
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20. Prediction of Persistence to Treatment for Patients with Rheumatoid Arthritis using Deep Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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). READ MORE
