Sökning: "stödvektormaskiner"

Visar resultat 1 - 5 av 17 uppsatser innehållade ordet stödvektormaskiner.

1. 1. An Evaluation of Classical and Quantum Kernels for Machine Learning Classifiers

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

   Författare :Teo Nordström; Jacob Westergren; [2023]
   Nyckelord :Machine Learning; Quantum Computing; Kernels; Support Vector Machines; Maskininlärning; Kvantberäkning; Kärnor; Stödvektormaskin;

   Sammanfattning : Quantum computing is an emerging field with potential applications in machine learning. This research project aimed to compare the performance of a quantum kernel to that of a classical kernel in machine learning binary classification tasks. LÄS MER

3. 2. ML enhanced interpretation of failed test result

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

   Författare :Hiranmayi Pechetti; [2023]
   Nyckelord :Data Parsing; Machine Learning; Log file Analysis; Text Classification; Supervised Classification; Dataanalys; maskininlärning; loggfilsanalys; textklassificering; Övervakad klassificering;

   Sammanfattning : 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. LÄS MER

4. 3. Classification of Flying Qualities with Machine Learning Methods

   Master-uppsats, KTH/Flygdynamik

   Författare :Ola Isaksson; [2021]
   Nyckelord :Flying Qualities; Machine Learning; Flight Mechanics; Flygkvaliteter; Maskininlärning; Flygmekanik;

   Sammanfattning : The primary objective of this thesis is to evaluate the prospect of machine learning methods being used to classify flying qualities based on simulator data (with the focus being on pitch maneuvers). If critical flying qualities could be identified earlier in the verification process, they can be further invested in and focused on with less cost for design changes of the flight control system. LÄS MER

5. 4. Can a Support Vector Machine identify poor performance of dyslectic children playing a serious game?

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

   Författare :Viktor Lemon; [2021]
   Nyckelord :Serious games; Dyslexia; Identifying; Performance; Support Vector Machines;

   Sammanfattning : This paper has been a part of developing the serious game Kunna, a web-based game with exercises targeting children diagnosed with dyslexia. This game currently consists of five different exercises aiming to practice reading and writing without a therapist or neuropsychologist present. LÄS MER

7. 5. A Comparative Analysis of Robustness to Noise in Machine Learning Classifiers

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

   Författare :Shotaro Ishii; David Ljunggren; [2021]
   Nyckelord :;

   Sammanfattning : Data that stems from real measurements often to some degree contain distortions. Such distortions are generally referred to as noise in machine learning terminology, and can lead to decreased classification accuracy and poor prediction results. LÄS MER