Sökning: "support vector machines"

Visar resultat 16 - 20 av 238 uppsatser innehållade orden support vector machines.

1. 16. Pilot Study on Working Memory : Investigating Single Trial Decoding to Find the Best Stimulus and Target for a Future Personalized Neurofeedback

   Master-uppsats, KTH/Medicinteknik och hälsosystem

   Författare :Erik Gasparini; [2023]
   Nyckelord :Visual working memory; Personalised neurofeedback; Visual stimulus; Targeted brain region.;

   Sammanfattning : A standard Neurofeedback approach to mitigate the working memory decline in some fragile groups (elderly, subjects affected by stroke or Alzheimer's disease) can be suboptimal for some patients. The goal of this research is to investigate which visual stimulus (among colour, geometrical shape, direction, and symbol) is the most suited for each of the six healthy participants and which brain areas are the most discriminative, during the maintenance of a presented stimulus in a retro-cue-based working memory experiment. LÄS MER

3. 17. Swedish Stock and Index Price Prediction Using Machine Learning

   Kandidat-uppsats, Mälardalens universitet/Akademin för utbildning, kultur och kommunikation

   Författare :Henrik Wik; [2023]
   Nyckelord :Stock Price Prediction; Machine Learning; Time Series Analysis; Linear Regression; K-Nearest Neighbors; Random Forest; Support Vector Machines; Neural Networks;

   Sammanfattning : Machine learning is an area of computer science that only grows as time goes on, and there are applications in areas such as finance, biology, and computer vision. Some common applications are stock price prediction, data analysis of DNA expressions, and optical character recognition. LÄS MER

4. 18. Classifying High-Growth Manufacturing Firms on the Swedish Stock Market:A Comparative Study Between the Logistic Regression, Support Vector Machine and Artificial Neural Network

   Master-uppsats, Lunds universitet/Nationalekonomiska institutionen

   Författare :William Fridström; [2023]
   Nyckelord :Machine Learning; Econometrics; Firm Growth; Binary Classification; Prediction; Model comparision.; Business and Economics;

   Sammanfattning : This is a comparative study between two modern machine learning algorithms, the Support Vector Machine and Artificial neural network, and one traditional econometric model, the Logistic regression. The main objective is to compare their performance by classifying high-growth companies. LÄS MER

5. 19. Benchmarking Machine Learning Methods for Peptide Activity Predictions

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Boel Knutson; Lida Meskini Moudi; [2022-10-14]
   Nyckelord :Drug discovery; peptide; classification; molecular representation; Z-scales; pseudo amino acid composition; one-hot representation; random forests; support vector machines;

   Sammanfattning : One of the main challenges in the drug discovery process is to find a suitable compound for further analysis. The compound must affect the target relevant for the specific disease, while at the same time have desired properties to make it a safe and efficient drug candidate. LÄS MER

7. 20. Predicting the size of a company winning a procurement: an evaluation study of three classification models

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Ellen Björkegren; [2022]
   Nyckelord :public procurement; classification; Linear Discriminant Analysis; Random Forests; Support Vector Machines;

   Sammanfattning : In this thesis, the performance of the classification methods Linear Discriminant Analysis (LDA), Random Forests (RF), and Support Vector Machines (SVM) are compared using procurement data to predict what size company will win a procurement. This is useful information for companies, since bidding on a procurement takes time and resources, which they can save if they know their chances of winning are low. LÄS MER