Sökning: "Random Forest classification"

Visar resultat 1 - 5 av 296 uppsatser innehållade orden Random Forest classification.

1. 1. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

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

   Författare :Anastasia Sarelli; [2024]
   Nyckelord :Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

   Sammanfattning : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. LÄS MER

3. 2. 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 differentialekvationer

   Författare :Patrik Gerdelius; Sjönneby Hugo; [2024]
   Nyckelord :Fraud Detection; User Behaviour; Random Forest; PCA; SMOTE;

   Sammanfattning : 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

4. 3. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

   Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Alexander Florean; [2024]
   Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

   Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

5. 4. Physical Exercise and Fatigue Detection using Machine Learning

   Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Filip Säterberg; Rasmus Nilsson; [2024]
   Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

   Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

7. 5. DISTRIBUTED ARTIFICIAL INTELLIGENCE FOR ANOMALY DETECTION IN A MODULAR MANUFACTURING ENVIRONMENT

   Magister-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

   Författare :Hana Hodzic; [2023]
   Nyckelord :;

   Sammanfattning : This thesis investigates anomaly detection and classification in a simulated modular manufacturingenvironment using Machine Learning algorithm Random Forest. This algorithm is tested on a localcomputer and an embedded device, specifically the Raspberry PI. LÄS MER