Sökning: "decision tree"

Visar resultat 26 - 30 av 342 uppsatser innehållade orden decision tree.

1. 26. Data Classification System Based on Combination Optimized Decision Tree : A Study on Missing Data Handling, Rough Set Reduction, and FAVC Set Integration

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

   Författare :Xuechun Lu; [2023]
   Nyckelord :Missing data handling; Rough set reduction; FAVC Set; ID3; Saknade datahantering; Rough set reducering; FAVC Set; ID3;

   Sammanfattning : Data classification is a novel data analysis technique that involves extracting valuable information with potential utility from databases. It has found extensive applications in various domains, including finance, insurance, government, education, transportation, and defense. LÄS MER

3. 27. Fault Detection in PV System using Machine Learning Technique

   Master-uppsats, Högskolan Dalarna/Mikrodataanalys

   Författare :Adhyapadi Apoorva Bhat; Jomin Koothenparambil Joy; [2023]
   Nyckelord :Machine learning; Fault Detection; Cluster; Regression model; PV System; Prediction; Solar Power; Renewable Energy;

   Sammanfattning : With the steady and rapid reliance on solar power as a viable alternative to traditional fuel-based energy, maintenance of solar panels is becoming an unavoidable issue for both producers and consumers. Machine learning techniques are useful in detecting solar panel faults and their life span. LÄS MER

4. 28. Event categorisation and Machine-learning Techniques in Searches for Higgs Boson Pairs in the ATLAS Experiment at the LHC

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Högenergifysik

   Författare :Milads Emadi; [2023]
   Nyckelord :Particle Physics; ATLAS; BDT; Boosted Decision Tree; Decision Tree; Optimization; Machine Learning; Analysis;

   Sammanfattning : This thesis investigates the pair production of Higgs bosons (di-Higgs events) at the ATLAS experiment in the Large Hadron Collider (LHC), focusing on the channel where one Higgs boson decays into two bottom quarks and the other decays into two tau leptons. The main objective was to determine whether introducing a split in the invariant mass of the decay products from the two Higgs bosons (the di-Higgs mass) and using this as an analysis variable improves the sensitivity of the Boosted Decision Tree (BDT) machine learning algorithm to the di-Higgs signal. LÄS MER

5. 29. A Comparative Analysis of Decision Tree Models in Identifying Landslide Susceptibility and Type Classification

   Kandidat-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Levi Jan Zuiverloon; [2023]
   Nyckelord :Landslides; landslide susceptibility mapping; Random Forest; Extreme Gradient Boosting; machine learning models; multiclass classification; binary classification; risk assessment; mitigation strategies; Italy; Aosta Valley; infrastructure vulnerability; supervised learning algorithms; Earth and Environmental Sciences;

   Sammanfattning : 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

7. 30. Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence

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

   Författare :Kevin Huang; [2023]
   Nyckelord :Text classification; Peer feedback; Explainable Artificial Intelligence; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM education; Textklassificering; Feedback till kamrater; Förklarig Artificiell Intelligens; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM-utbildning;

   Sammanfattning : Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings, including the setting of engineering education, in which collaborative teaching and learning activities are common. LÄS MER