Sökning: "feature engineering"
Visar resultat 1 - 5 av 319 uppsatser innehållade orden feature engineering.
1. Improving feature discoverability in continuously deployed software products
Master-uppsats, Lunds universitet/Institutionen för datavetenskapSammanfattning : .... LÄS MER
2. Using Synthetic Data For Object Detection on the edge in Hazardous Environments
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : This thesis aims to evaluate which aspects are important when generating synthetic data with the purpose of running on a lightweight object detection model on an edge device. The task we constructed was to detect Canisters and whether they feature a protective valve called a Cap or not (called a No-Cap). LÄS MER
3. Simulation-based discrimination of Crab pulsar models with XL-Calibur
Master-uppsats, KTH/FysikSammanfattning : Polarisation of X-ray light is being investigated with polarimeters to extend the borders of what can be observed. Distant compact objects, such as pulsars, that are to small on the sky to be analysed with imaging can be investigated by analysing the polarisation of the emitted light. This can reveal physics previously hidden by their small nature. LÄS MER
4. Potential and Limitations of the Sketch Map Tool in the International Red Cross Red Crescent Movement
Master-uppsats, Lunds universitet/Avdelningen för Riskhantering och SamhällssäkerhetSammanfattning : In disaster risk management, participatory mapping (PM) closes spatial data gaps in communities by integrating local risk knowledge. The thesis examined the potential and limitations of the Sketch Map Tool (SMT) as a PM tool for community-based disaster risk reduction (DRR) through an International Red Cross Red Crescent Movement case study. LÄS MER
5. Detecting Fraudulent User Behaviour : A Study of User Behaviour and Machine Learning in Fraud Detection
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Analys och partiella differentialekvationerSammanfattning : This study aims to create a Machine Learning model and investigate its performance of detecting fraudulent user behaviour on an e-commerce platform. The user data was analysed to identify and extract critical features distinguishing regular users from fraudulent users. LÄS MER