Sökning: "Extreme Gradient Boosting"
Visar resultat 1 - 5 av 33 uppsatser innehållade orden Extreme Gradient Boosting.
1. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. LÄS MER
2. Multi-Class Classification for Predicting Customer Satisfaction : Application of machine learning methods to predict customer satisfaction at IKEA
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : Gaining a comprehensive understanding of the features that contribute to customer satisfaction after contact with IKEA’s Remote Customer Meeting Points (RCMPs) is essential for implementing effective remedial measures in the future. The aim of this project is to investigate if it is possible to find key features that influence customer satisfaction and to use these to predict customer satisfaction. LÄS MER
3. Machine Learning of Laser Ultrasonic Data to Predict Material Properties
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : The hardness of steel is an important quality parameter for several industrial applications. Conventional mechanical testing is used in quality testing for material hardness and the method is time-consuming, can cause material mix-ups, and results in material waste. LÄS MER
4. A Comparative Analysis of Decision Tree Models in Identifying Landslide Susceptibility and Type Classification
Kandidat-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Landslides pose a significant risk to human life and infrastructure, especially in Italy, which has a high frequency of landslide occurrences. To mitigate these hazards, Landslide Susceptibility Mapping (LSM) is crucial for identifying risk areas and developing appropriate mitigation strategies. LÄS MER
5. Predicting Short-term Absences of a Railway Crew using Historical Data
Master-uppsats, KTH/Matematisk statistikSammanfattning : Transportation via train is considered the most environmentally friendly way of traveling and is widely seen as the future of transportation. Canceled and delayed trains worsen customer satisfaction; thus, punctual trains are crucial for railway companies. LÄS MER