Sökning: "K-NN"

Visar resultat 16 - 20 av 44 uppsatser innehållade ordet K-NN.

  1. 16. Maskininlärning för diagnosticering av perifer neuropati

    Kandidat-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Margareta Carlerös; Nina Malmqvist; Josefin Nilsson; Fredrik Skärberg; [2019-07-02]
    Nyckelord :Klassificering; AI; Statistiskinlärning; k-NN; Slumpmässig skog; Neurala nätverk; Medicinsk diagnostik; Dynamiskt Svettest;

    Sammanfattning : This report investigates the possibility of diagnosing peripheral neuropathy with the help of non-parametic classification methods. Peripheral neuropathy is a disease state characterized by damage on the nerves furthest out in the nervous system, with symptoms first occuring in the feet. The data used in this project comes from Dr. LÄS MER

  3. 17. Predicting house prices with machine learning methods

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

    Författare :Isak Engström; Alan Ihre; [2019]
    Nyckelord :;

    Sammanfattning : In this study, the machine learning algorithms k-Nearest-Neighbours regression (k-NN) and Random Forest (RF) regression were used to predict house prices from a set of features in the Ames housing data set. The algorithms were selected from an assessment of previous research and the intent was to compare their relative performance at this task. LÄS MER

  4. 18. Crime Prediction in Swedish Municipalities with machine learning algorithms

    Kandidat-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Nils Dominguez Berndtsson; [2019]
    Nyckelord :Crime rates; machine learning algorithms; Random forest; K-NN; Mathematics and Statistics;

    Sammanfattning : In this thesis we use a number of common machine learning algorithms to predict crime rates in Swedish municipalities. As predictors we use a mix of municipal socioeconomic variables. For some years we are able to correctly classify up to 85% of the municipalities that have a high crime rate. LÄS MER

  5. 19. Fraud or Not?

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Thea Åkerblom; Tobias Thor; [2019]
    Nyckelord :Logistic Regression; K-Nearest Neighbour; classification; random forest; fraud; transactions and statistical learning;

    Sammanfattning : This paper uses statistical learning to examine and compare three different statistical methods with the aim to predict credit card fraud. The methods compared are Logistic Regression, K-Nearest Neighbour and Random Forest. LÄS MER

  7. 20. Inomhuspositionering med bredbandig radio

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

    Författare :Oscar Gustavsson; Adam Miksits; [2019]
    Nyckelord :Indoor Localisation; WiFi-fingerprinting; k-Nearest Neighbour; RSSI; CSI;

    Sammanfattning : In this report it is evaluated whether a higher dimensional fingerprint vector increases accuracy of an algorithm for indoor localisation. Many solutions use a Received Signal Strength Indicator (RSSI) to estimate a position. It was studied if the use of the Channel State Information (CSI), i.e. LÄS MER