Sökning: "algorithm selection"

Visar resultat 1 - 5 av 205 uppsatser innehållade orden algorithm selection.

  1. 1. Compressed Machine Learning on Time Series Data

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Felix Finger; Nathalie Gocht; [2020-07-08]
    Nyckelord :time series clustering; large scale data; machine learning; prediction; anomaly detection; compression;

    Sammanfattning : The extent of time related data across many fields has led to substantial interestin the analysis of time series. This interest meets growing challenges to store andprocess data. While the data is collected at an exponential rate, advancements inprocessing units are slowing down. LÄS MER


    Kandidat-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Robin Johansson; [2020]
    Nyckelord :;

    Sammanfattning : Feature selection is an important step regarding Electroencephalogram (EEG) classification, for a Brain-Computer Interface (BCI) systems, related to Motor Imagery (MI), due to large amount of features, and few samples. This makes the classification process computationally expensive, and limits the BCI systems real-time applicability. LÄS MER

  3. 3. Predicting Multimodal Rehabilitation Outcomes using Machine Learning

    Kandidat-uppsats, Uppsala universitet/Institutionen för informatik och media; Uppsala universitet/Institutionen för informatik och media

    Författare :Alexandru Cheltuitor; Niklas Jones-Quartey; [2020]
    Nyckelord :Machine learning; XGBoost; regression; Multimodal Rehabilitation; SQRP; chronic pain; treatment outcome; prediction;

    Sammanfattning : Chronic pain is a complex health issue and a major cause of disability worldwide. Although multimodal rehabilitation (MMR) has been recognized as an effective form of treatment for chronic pain, some patients do not benefit from it. LÄS MER

  4. 4. The impact of distance, feature weighting and selection for KNN in credit default prediction

    Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

    Författare :Huicheng Zhang; [2020]
    Nyckelord :;

    Sammanfattning : With the rapid spread of credit card business around the world, credit risk has also expanded dramatically. The occurrence of a large number of credit cardcustomer defaults has caused huge losses to financial institutions such as banks. Therefore, it is particularly important to accurately identify default customers. LÄS MER

  5. 5. Modelling default probabilities: The classical vs. machine learning approach

    Master-uppsats, KTH/Matematisk statistik; KTH/Matematisk statistik

    Författare :Filip Janovic; Paul Singh; [2020]
    Nyckelord :Machine learning; gradient boosting; pd-modelling; CatBoost; Random Forest; Logistic Regression; Maskininlärning; gradient boosting; fallissemangmodellering; CatBoost; Random Forest; Logistisk Regression;

    Sammanfattning : Fintech companies that offer Buy Now, Pay Later products are heavily dependent on accurate default probability models. This is since the fintech companies bear the risk of customers not fulfilling their obligations. LÄS MER