Browsing by Subject "Machine Learning"
Now showing items 1-6 of 6
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An application of Data Mining Classification Techniques to Electricity Fraud Detection; A Case of Umeme (U) Ltd
(2021-11)The main objective of this research was to develop a suitable classification model that will be able to identify and predict customers with fraudulent consumption. This research addresses the lack of effective methods for ... -
Availability Estimation of Power Generating Units at Nalubaale Power Station.
(Makerere University, 2023-01)The main aim of an electric power system is to reliably provide electrical power supply to customers. However, in 2020, Uganda’s grid experienced an average of 62.4% forced outages. The forced outages due to generator ... -
A detection model for user-to-root attacks using the AdaBoost classifier
(Makerere University, 2021-10-06)Intrusion detection in enterprise networks is a key area of interest in computer security today because of its importance and vast application, such as detection of attacks by legal users. Current attack ... -
Estimating Carbon Stock using field data, Satellite Imagery, and Cloud-Based Machine Learning Algorithms: case study of Mubende District
(Makerere University, 2023-01)Quantifying carbon stock is a good step in pursuit to mitigate GreenHouse Gases (GHGs). The purpose of this research was to estimate carbon stock changes in Mubende District as a consequence of Land Cover Change (LCC) ... -
A machine learning approach to predict E. coli antibacterial resistance using whole-genome sequencing data
(Makerere University, 2023)Background: Antimicrobial resistance (AMR) is a significant global health threat, particularly impacting low- and middle-income countries(LMICS) such as Uganda, where reliable and rapid methods for detecting AMR in E. coli ... -
Predicting switch to second-line antiretroviral therapy regimen: A comparison of the traditional linear classification methods and advance nonlinear machine learning algorithms
(Makerere University, 2022)Introduction: Due to changes in data patterns, self-learning approaches have been adopted in research which is commonly known as Machine Learning (ML). ML has been used previously to predict health outcomes such as early ...