Sökning: "k-NN"

Visar resultat 26 - 30 av 44 uppsatser innehållade ordet k-NN.

  1. 26. Evaluation of Machine Learning Classification Methods : Support Vector Machines, Nearest Neighbour and Decision Tree

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Sebastian Stiernborg; Sara Ervik; [2017]
    Nyckelord :;

    Sammanfattning : With more and more data available, the interest and use for machine learning is growing and so does the need for classification. Classifica- tion is an important method within machine learning for data simpli- fication and prediction. LÄS MER

  3. 27. Machine learning and its applications within insurance hit rates and credit risk modelling

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Linus Blomgren; Hampus Vitestam; [2017]
    Nyckelord :Machine learning; Artificial intelligence; Insurance; Credit risk; SMOTE; k-NN; Naïve Bayes; Decision tree; Random forest; Support vector machine; Neural network; Generalized linear model; Receiver operating characteristics; Hit rate; Mathematics and Statistics;

    Sammanfattning : This thesis aims to shine light on some different machine learning methods. As reference a more common statistical prediction method, namely the generalized linear model, is applied to compare the results of the machine learning methods. Six different machine learning methods are investigated. LÄS MER

  4. 28. Evaluating Stress through Machine Learning based on Brain Activity Data

    Kandidat-uppsats, KTH/Skolan för elektro- och systemteknik (EES)

    Författare :Christian Agnér; Anneli Blomqvist; [2017]
    Nyckelord :;

    Sammanfattning : More people are experiencing stressrelatedsymptoms, which is not only causing worsenhealth, but also causing economical drawbacks for thesociety, businesses and individuals. The aim of thisproject is to create a tool that evaluates stress frombrain activity data and can help to avoid develop thesymptoms. LÄS MER

  5. 29. Evaluation of system design strategies and supervised classification methods for fruit recognition in harvesting robots

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Gabriella Björk; [2017]
    Nyckelord :Supervised Machine Learning; Classification; Image Processing; Computer Vision; Support Vector Machine; k-Nearest Neighbor; Decision Tree; Harvesting Robot; Recognition System; Kinect v2; Maskininl¨arning; Klassifikation; Bildprocessering; Dataseende; Support Vector Machine; k-Nearest Neighbor; Decision Tree; Sk¨orderobot; Igenk¨anningssystem; Kinect v2;

    Sammanfattning : This master thesis project is carried out by one student at the Royal Institute of Technology in collaboration with Cybercom Group. The aim was to evaluate and compare system design strategies for fruit recognition in harvesting robots and the performance of supervised machine learning classification methods when applied to this specific task. LÄS MER

  7. 30. Cold-start recommendations for the user- and item-based recommender systemalgorithm k-Nearest Neighbors

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Robert Lorentz; Oskar Ek; [2017]
    Nyckelord :Cold start; Recommender system; K-NN;

    Sammanfattning : Recommender systems apply machine learning methods to solve the task of providing appropriate suggestions to users in both static and dynamic environments. An example of this is a movie service like Netflix that recommends movies to its users. LÄS MER