Sökning: "gradient boosting regression tree"

Visar resultat 1 - 5 av 14 uppsatser innehållade orden gradient boosting regression tree.

  1. 1. Evaluation of Machine Learning Classifiers for Refractory Epilepsy Classification

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

    Författare :Ann Abeysekera; Elina Tayebi; [2023]
    Nyckelord :;

    Sammanfattning : Epilepsy is a neurological disease, where up to 40% of patients, known as having refractory epilepsy, do not become seizure-free through antiepileptic drugs (AEDs). Epilepsy surgery has the highest possibility of treating patients with refractory epilepsy, however, many are never referred to surgical evaluation. LÄS MER

  3. 2. Modeling Melodic Accents in Jazz Solos

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

    Författare :Misael Berrios Salas; [2023]
    Nyckelord :Accents; Jazz Solo; Support Vector Regression SVR ; eXtreme Gradient Boosting XGBoost ; Multiple Linear Regression MLR ; Dynamic; Accenter; Jazz Solos; Support Vector Regression SVR ; eXtreme Gradient Boosting XGBoost ; Multiple Linear Regression MLR ; Dynamisk;

    Sammanfattning : This thesis looks at how accurately one can model accents in jazz solos, more specifically the sound level. Further understanding the structure of jazz solos can give a way of pedagogically presenting differences within music styles and even between performers. Some studies have tried to model perceived accents in different music styles. LÄS MER

  4. 3. Predicting IPO Underpricing: A study on the predictability of IPO underpricing through machine learning algorithms

    C-uppsats, Handelshögskolan i Stockholm/Institutionen för redovisning och finansiering

    Författare :Victor Holgersson; Axel Tardell; [2023]
    Nyckelord :IPO Underpricing; Machine Learning; Neural Network; Random Forest; Gradient-Boosting Trees;

    Sammanfattning : This paper primarily serves to examine whether a specific subset of variables, derived from publicly available pre-IPO data, can be effectively modeled to predict and classify if an IPO will be underpriced using non-linear machine learning (ML) models. Secondly, we analyze whether the performance of ML-based models is greater compared to conventional linear models. LÄS MER

  5. 4. Maskininlärning med konform förutsägelse för prediktiva underhållsuppgifter i industri 4.0

    Master-uppsats, Jönköping University/JTH, Avdelningen för datavetenskap

    Författare :Shuzhou Liu; Mpova Mulahuko; [2023]
    Nyckelord :Machine Learning; Deep Learning; Uncertainty estimation; Conformal prediction; Predictive maintenance; RUL; Probabilistic predictions; Decision Tree; Random Forest; Support Vector Regression; Gradient Boosting; LSTM;

    Sammanfattning : This thesis is a cooperation with Knowit, Östrand \& Hansen, and Orkla. It aimed to explore the application of Machine Learning and Deep Learning models with Conformal Prediction for a predictive maintenance situation at Orkla. Predictive maintenance is essential in numerous industrial manufacturing scenarios. LÄS MER

  7. 5. Prediction of Stock Returns Using Accounting Data with a Machine Learning Approach

    Master-uppsats, Göteborgs universitet/Graduate School

    Författare :Ludvig Ekmark; Tobias Frisell; [2022-06-30]
    Nyckelord :Stock price prediction; Accounting data; Machine learning; Gradient boosting decision trees; CatBoost classifier; Logistic regression; Feature importance;

    Sammanfattning : The relationship between accounting data and stock price prediction has been a hot topic for over half a century. Researchers have been trying to identify the relationship and investigate how it may be useful when trying to improve prediction accuracy. LÄS MER