Sökning: "Statistisk inlärning"

Visar resultat 1 - 5 av 20 uppsatser innehållade orden Statistisk inlärning.

  1. 1. Modeling Success Factors for Start-ups in Western Europe through a Statistical Learning Approach

    Master-uppsats, KTH/Industriell ekonomi och organisation (Inst.); KTH/Industriell ekonomi och organisation (Inst.)

    Författare :Adib Kamal; Kenan Sabani; [2021]
    Nyckelord :Machine learning; KNN; Random Forest; Logistic Regression; Start-up; Success; Maskininlärning; KNN; Random Forest; Logistic Regression; Start-up; Framgångsfaktorer;

    Sammanfattning : The purpose of this thesis was to use a quantitative method to expand on previous research in the field of start-up success prediction. This was accomplished by including more criteria in the study, which was made possible by the Crunchbase database, which is the largest available information source for start-ups. LÄS MER

  2. 2. Supervised Learning for Prediction of Tumour Mutational Burden

    Master-uppsats, KTH/Matematisk statistik

    Författare :Joanna Hargell; [2021]
    Nyckelord :Supervised Learning; Tumour Mutational Burden; Generalized Linear Models; Decision trees; Support Vector Machines; statistik; tillämpad matematik; statistisk inlärning; mutationsbörda;

    Sammanfattning : Tumour Mutational Burden is a promising biomarker to predict response to immunotherapy. In this thesis, statistical methods of supervised learning were used to predict TMB: GLM, Decision Trees and SVM. LÄS MER

  3. 3. Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces

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

    Författare :Christopher Herron; André Zachrisson; [2020]
    Nyckelord :Applied Mathematics; Machine Learning; Statistics; Gaussian Process; Neural Network; Options; Volatility; Implied Volatility Surface; Black Scholes; Tillämpad matematik; Maskininlärning; Statistik; Gaussisk Process; Neurala Nätverk; Optioner; Volatilitet; Implicit Volatilitetsyta; Black Scholes;

    Sammanfattning : The implied volatility surface plays an important role for Front office and Risk Management functions at Nasdaq and other financial institutions which require mark-to-market of derivative books intraday in order to properly value their instruments and measure risk in trading activities. Based on the aforementioned business needs, being able to calibrate an end of day implied volatility surface based on new market information is a sought after trait. LÄS MER

  4. 4. Synthesis of Tabular Financial Data using Generative Adversarial Networks

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

    Författare :Anton Karlsson; Torbjörn Sjöberg; [2020]
    Nyckelord :Generative Adversarial Networks; GAN; Generative Modeling; Tabular data; Financial data; Machine Learning; Statistical learning; Applied Mathematics; GANs; Generativa modeller; Tabulär data; Finansdata; Maskininlärning; Statistisk inlärning; Tillämpad Matematik;

    Sammanfattning : Digitalization has led to tons of available customer data and possibilities for data-driven innovation. However, the data needs to be handled carefully to protect the privacy of the customers. Generative Adversarial Networks (GANs) are a promising recent development in generative modeling. LÄS MER

  5. 5. Early-Stage Prediction of Lithium-Ion Battery Cycle Life Using Gaussian Process Regression

    Master-uppsats, KTH/Matematisk statistik

    Författare :Love Wikland; [2020]
    Nyckelord :Statistical learning; prediction; regression; Gaussian processes; lithium-ion battery; battery health; battery lifetime; Statistisk inlärning; prediction; regression; Gaussiska processer; litiumjonbatteri; batterihälsa; batterilivstid;

    Sammanfattning : Data-driven prediction of battery health has gained increased attention over the past couple of years, in both academia and industry. Accurate early-stage predictions of battery performance would create new opportunities regarding production and use. LÄS MER