Sökning: "kernel methods"

Visar resultat 1 - 5 av 70 uppsatser innehållade orden kernel methods.

  1. 1. Tidsserie regression på finansmarknaden

    Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI); KTH/Skolan för teknikvetenskap (SCI)

    Författare :Daniel Hirsch; Tim Steinholtz; [2019]
    Nyckelord :;

    Sammanfattning : I den här rapporten studerar vi prestanda för två maskininlärningsalgoritmer när de implementeras för prisförutsättningar på den svenska elmarknaden. Målet med detta projekt är att utvärdera om dessa algoritmer kan användas som verktyg för investeringar. LÄS MER

  2. 2. Att förutspå Sveriges bistånd : En jämförelse mellan Support Vector Regression och ARIMA

    Kandidat-uppsats, Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Författare :Max Wågberg; [2019]
    Nyckelord :Machine-learning; Python; ARIMA; SVR; Timeseries; Regression; Maskininlärning; Python; ARIMA; SVR; Tidsserie; Regression;

    Sammanfattning : In recent years, the use of machine learning has increased significantly. Its uses range from making the everyday life easier with voice-guided smart devices to image recognition, or predicting the stock market. Predicting economic values has long been possible by using methods other than machine learning, such as statistical algorithms. LÄS MER

  3. 3. Positivity of Heat Kernels

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Manne Milton; [2019]
    Nyckelord :;

    Sammanfattning : Partial di˙erential equations are a well-studied field of mathematics, and in this thesis we attempt to use some of the newer methods, including path integrals (also known as Feynman path integrals) and the so-called geometric approach, to find conditions for the heat kernel of a di˙erential operator on a certain form to be zero. We also derive a maximum principle, more general than the classical one, that allows for degenerate di˙erential operators, where the degeneracy is controlled by a Muckenhoupt weight. LÄS MER

  4. 4. Machine Learning for Market Prediction : Soft Margin Classifiers for Predicting the Sign of Return on Financial Assets

    Master-uppsats, Linköpings universitet/Produktionsekonomi; Linköpings universitet/Produktionsekonomi

    Författare :George Abo Al Ahad; Abbas Salami; [2018]
    Nyckelord :Machine Learning; Finance; Financial Time Series; Support Vector Machines; Relevance Vector Machines; Multiple Kernel Learning; Simulated Annealing; SVM; RVM; MKL; SA; FSVM; TSVM; FTSVM;

    Sammanfattning : Forecasting procedures have found applications in a wide variety of areas within finance and have further shown to be one of the most challenging areas of finance. Having an immense variety of economic data, stakeholders aim to understand the current and future state of the market. LÄS MER

  5. 5. The use of spatial and temporal analysis in the maintenance of road mortality mitigation measures for wildlife in Ireland

    Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknik

    Författare :Aoife Moroney; [2018]
    Nyckelord :roadkill; wildlife crossing; hotspot analysis; ripley s k; KDE; SANET;

    Sammanfattning : Urbanisation and a growing global population have caused our road networks to expand rapidly in the past decades. The consequences of transport infrastructure for wildlife include traffic mortality, habitat loss and habitat degradation and the negative impact of a road extends far beyond the road itself. LÄS MER