Sökning: "bayesianska nätverk"

Visar resultat 1 - 5 av 28 uppsatser innehållade orden bayesianska nätverk.

1. 1. Predicting Patent Data using Wavelet Regression and Bayesian Machine Learning

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Mattias Martinsen; [2023]
   Nyckelord :Wavelet; Regression; Bayesian network; Prediction; Patent; Machine Learning; Wavelet; Regression; Bayesiskt nätverk; Predicering; Patent; Maskininlärning;

   Sammanfattning : Patents are a fundamental part of scientific and engineering work, ensuringprotection of inventions owned by individuals or organizations. Patents areusually made public 18 months after being filed to a patent office, whichmeans that current publicly available patent data only provides informationabout the past. LÄS MER

3. 2. Bayesian Networks for Modelling the Respiratory System and Predicting Hospitalizations

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

   Författare :Victor Lopo Martinez; [2023]
   Nyckelord :Bayesian Networks; Structure Learning; Conditional Probability Tables; Maximum Likelihood Estimator; XGBoost; and Respiratory System; Bayesianska nätverk; Strukturinlärning; Villkorliga sannolikhetstabeller; Maximum Likelihood Estimator; XGBoost; och Andningssystemet;

   Sammanfattning : Bayesian networks can be used to model the respiratory system. Their structure indicate how risk factors, symptoms, and diseases are related and the Conditional Probability Tables enable predictions about a patient’s need for hospitalization. LÄS MER

4. 3. LDPC DropConnect

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

   Författare :Xi Chen; [2023]
   Nyckelord :Bayesian approach; Machine learning; Coding theory; Measurement uncertainty; Algorithms; Bayesiansk metod; Maskininlärning; Kodningsteori; Mätosäkerhet; Algoritmer;

   Sammanfattning : Machine learning is a popular topic that has become a scientific research tool in many fields. Overfitting is a common challenge in machine learning, where the model fits the training data too well and performs poorly on new data. LÄS MER

5. 4. Non-Bayesian Out-of-Distribution Detection Applied to CNN Architectures for Human Activity Recognition

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

   Författare :Serghei Socolovschi; [2022]
   Nyckelord :Human Activity Recognition; Deep Learning; Time Series; Uncertainty Estimation; Outofdistribution Detection; Convolutional Neural Network; Human Activity Recognition; Deep Learning; Tidsserie; Uppskattning av Osäkerheten; Outofdistribution Detection; Convolutional Neural Network;

   Sammanfattning : Human Activity Recognition (HAR) field studies the application of artificial intelligence methods for the identification of activities performed by people. Many applications of HAR in healthcare and sports require the safety-critical performance of the predictive models. LÄS MER

7. 5. Causal Inference on Tactical Simulations using Bayesian Structure Learning

   Master-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

   Författare :Karl Lagerkvist Blomqvist; [2022]
   Nyckelord :Causal Inference; Bayesian Structure Learning; Do-Calculus; Tactical Simulations; Kausal Inferens; Bayesiansk Strukturinlärning; Do-Calculus; Taktiska Simuleringar;

   Sammanfattning : This thesis explores the possibility of using Bayesian Structure Learning and Do-Calculus to perform causal inference on data from tactical combat simulations provided by Saab. A four-step approach is considered whose first step is to find a Bayesian Network from the data using Bayesian Structure Learning and Probability Distribution Fitting. LÄS MER