Sökning: "klassificeringsträd"

Visar resultat 1 - 5 av 6 uppsatser innehållade ordet klassificeringsträd.

  1. 1. Decision Trees for Classification of Repeated Measurements

    Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

    Författare :Julianna Holmberg; [2024]
    Nyckelord :Repeated Measurement Data; Growth Curve Model; Linear Discriminant Analysis; Decision Tree; Bootstrap Aggregating; CART; CART-LC;

    Sammanfattning : Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. LÄS MER

  3. 2. Predicting Stock Price Direction for Asian Small Cap Stocks with Machine Learning Methods

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Tina Abazari; Sherwin Baghchesara; [2021]
    Nyckelord :Machine Learning; Classification; Classification Trees; Random Forest; Support Vector Machine; Logistic Regression; Stocks; Stock Market; Asset Management; Investments; Asia; Small Cap; Micro Cap; Maskininlärning; Klassificering; Klassificeringsträd; Random Forest; Support Vector Machine; Logistisk Regression; Aktier; Aktiemarknad; Fondförvaltning; Investeringar; Asien; Småbolag; Mikrobolag.;

    Sammanfattning : Portfolio managers have a great interest in detecting high-performing stocks early on. Detecting outperforming stocks has for long been of interest from a research as well as financial point of view. Quantitative methods to predict stock movements have been widely studied in diverse contexts, where some present promising results. LÄS MER

  4. 3. MLSurf : Surfer Motion Characterization Using Machine Learning Techniques

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

    Författare :Dániel Bányay; [2019]
    Nyckelord :;

    Sammanfattning : Wave surfing is a popular sport that requires minimal financial investment, while it can still be enjoyable from the very first attempt. At the same time, the demand for smart devices that enhance the experience of doing sports by analyzing and evaluating the activities is growing. LÄS MER

  5. 4. Ditch detection using refined LiDAR data : A bachelor’s thesis at Jönköping University

    Kandidat-uppsats, Högskolan i Jönköping/JTH, Datateknik och informatik

    Författare :Jonatan Flyckt; Filip Andersson; [2019]
    Nyckelord :machine learning; geographic information systems; GIS; classification trees; supervised learning; maskininlärning; geografiska informationssystem; GIS; klassificeringsträd; övervakat lärande;

    Sammanfattning : In this thesis, a method for detecting ditches using digital elevation data derived from LiDAR scans was developed in collaboration with the Swedish Forest Agency. The objective was to compare a machine learning based method with a state-of-the-art automated method, and to determine which LiDAR-based features represent the strongest ditch predictors. LÄS MER

  7. 5. Hur relaterar det optimala valet av klassificeringsmetod till datamaterialets egenskaper? : En jämförande studie mellan logistisk regression, elastic net och boosting tillämpat på klassificeringsträd.

    Kandidat-uppsats, Umeå universitet/Statistik

    Författare :Blaise Ngendangenzwa; Jonathan Sundin; [2015]
    Nyckelord :;

    Sammanfattning : På sistone har allt mer kritik riktats mot forskning inom klassificering. Trots att forskningen har resulterat i en uppsjö av klassificeringsmetoder finns det de som menar att den har varit ett misslyckande och pekar på det faktum att ingen klassificeringsmetod anses vara systematiskt bättre än den andra eller ens rena gissningar. LÄS MER