Sökning: "cross-validation"

Visar resultat 21 - 25 av 252 uppsatser innehållade ordet cross-validation.

  1. 21. Predicting Airbnb Prices in European Cities Using Machine Learning

    Kandidat-uppsats, Blekinge Tekniska Högskola/Fakulteten för datavetenskaper

    Författare :Shalini Gangarapu; Venkata Surya Akash Mernedi; [2023]
    Nyckelord :Machine Learning; Supervised Learning; Regression Algorithms; Airbnb Price Prediction;

    Sammanfattning : Background: Machine learning is a field of computer science that focuses on creating models that can predict patterns and relations among data. In this thesis, we use machine learning to predict Airbnb prices in various European cities to help the hosts in setting reasonable prices for their properties. LÄS MER

  3. 22. Uncertainty Analysis : Severe Accident Scenario at a Nordic Nuclear Power Plant

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Josefin Hedly; Mikaela De Young; [2023]
    Nyckelord :Nuclear power plant; microdata analysis; Random Forest; k-Nearest Neighbor; SVM;

    Sammanfattning : Nuclear Power Plants (NPP) undergo fault and sensitivity analysis with scenario modelling to predict catastrophic events, specifically releases of Cesium 137 (Cs-137). The purpose of this thesis is to find which of 108 input-features from Modular Accident Analysis Program (MAAP)simulation code are important, when there is large release of Cs-137 emissions. LÄS MER

  4. 23. Neural Networks for Modeling of Electrical Parameters and Losses in Electric Vehicle

    Magister-uppsats, Högskolan i Skövde/Institutionen för ingenjörsvetenskap

    Författare :Yo Fujimoto; [2023]
    Nyckelord :Artificial neural network; machine learning; random forest; deep learning; electric vehicle; decision tree; k-nearest neighbors; permanent magnet synchronous machine;

    Sammanfattning : Permanent magnet synchronous machines have various advantages and have showed the most superiorperformance for Electric Vehicles. However, modeling them is difficult because of their nonlinearity. LÄS MER

  5. 24. Evaluating Random Forest and k-Nearest Neighbour Algorithms on Real-Life Data Sets

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

    Författare :Atheer Salim; Milad Farahani; [2023]
    Nyckelord :Random Forest; k-Nearest Neighbour; Evaluation; Machine Learning; Classification; Execution Time; Slumpmässig Skog; k-Närmaste Granne; Utvärdering; Maskininlärning; Klassificiering; Exekveringstid;

    Sammanfattning : Computers can be used to classify various types of data, for example to filter email messages, detect computer viruses, detect diseases, etc. This thesis explores two classification algorithms, random forest and k-nearest neighbour, to understand how accurately and how quickly they classify data. LÄS MER

  7. 25. Beyond the Big Five Factors: Using Facets and Nuances for Enhanced Prediction in Life Outcomes

    Master-uppsats, Lunds universitet/Institutionen för psykologi

    Författare :Maiken Due Nielsen; [2023]
    Nyckelord :Personality traits; IPIP-NEO; facets; nuances; items; life outcomes; predictive validity; Social Sciences;

    Sammanfattning : Objective: Previous research using personality traits to predict life outcomes has typically utilized the Big Five factors and, occasionally, their facets. However, recent research suggests that using items (reflecting personality nuances) can account for greater predictive variance. LÄS MER