Sökning: "överanpassning"

Visar resultat 1 - 5 av 10 uppsatser innehållade ordet överanpassning.

  1. 1. Deep Learning för klassificering av kundsupport-ärenden

    Uppsats för yrkesexamina på grundnivå, Högskolan i Gävle/Datavetenskap

    Författare :Max Jonsson; [2020]
    Nyckelord :Natural Language Processing; Text Classification; Convolutional Neural Network; Long Short Time Memory; Naturlig språkbehandling; Textklassificering; Convolutional Neural Network; Long Short Time Memory;

    Sammanfattning : Företag och organisationer som tillhandahåller kundsupport via e-post kommer över tid att samla på sig stora mängder textuella data. Tack vare kontinuerliga framsteg inom Machine Learning ökar ständigt möjligheterna att dra nytta av tidigare insamlat data för att effektivisera organisationens framtida supporthantering. LÄS MER

  2. 2. A Comparative study of data splitting algorithms for machine learning model selection

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

    Författare :Delwende Eliane Birba; [2020]
    Nyckelord :K-fold; cross-validation; Kennard-Stone algorithm; data splitting; bootstrap; overfitting; SPXY; k-faldig korsvalidering; korsvalidering; Kennard-Stone-algoritm; datapartitionering; bootstrap; överanpassning; SPXY;

    Sammanfattning : Data splitting is commonly used in machine learning to split data into a train, test, or validation set. This approach allows us to find the model hyper-parameter and also estimate the generalization performance. In this research, we conducted a comparative analysis of different data partitioning algorithms on both real and simulated data. LÄS MER

  3. 3. Graph theory applications in the energy sector : From the perspective of electric utility companies

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

    Författare :Kristofer Espinosa; Tam Vu; [2020]
    Nyckelord :graph theory; feature selection; energy industry; grafteori; variabelselektering; energiindustri;

    Sammanfattning : Graph theory is a mathematical study of objects and their pairwise relations, also known as nodes and edges. The birth of graph theory is often considered to take place in 1736 when Leonhard Euler tried to solve a problem involving seven bridges of Königsberg in Prussia. LÄS MER

  4. 4. Applications of graph theory in the energy sector, demonstrated with feature selection in electricity price forecasting

    Master-uppsats, KTH/Optimeringslära och systemteori

    Författare :Duc Tam Vu; [2020]
    Nyckelord :Graph theory; feature selection; energy company; Grafteori; variabelselektering; energiföretag;

    Sammanfattning : Graph theory is a mathematical study of objects and their pairwise relations, known as nodes and edges respectively. The birth of graph theory is often considered to take place in 1736 when the Swiss mathematician Leonhard Euler tried to solve a routing problem involving seven bridges of Königsberg in Prussia. LÄS MER

  5. 5. Bayesian Neural Networks for Financial Asset Forecasting

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

    Författare :Alexander Back; William Keith; [2019]
    Nyckelord :Bayesian neural networks; variational inference; Markov chain Monte Carlo; dropout; systematic trading; futures contracts; Bayesianska neurala nätverk; variational inference; Markov chain Monte Carlo; dropout; systematisk trading; terminskontrakt;

    Sammanfattning : Neural networks are powerful tools for modelling complex non-linear mappings, but they often suffer from overfitting and provide no measures of uncertainty in their predictions. Bayesian techniques are proposed as a remedy to these problems, as these both regularize and provide an inherent measure of uncertainty from their posterior predictive distributions. LÄS MER