Essays about: "Gradient boosting decision trees"

Showing result 1 - 5 of 11 essays containing the words Gradient boosting decision trees.

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

   University essay from Göteborgs universitet/Graduate School

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

   Abstract : 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. READ MORE

3. 2. Anticipating bankruptcies among companies with abnormal credit risk behaviour : Acase study adopting a GBDT model for small Swedish companies

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Simon Heinke; [2022]
   Keywords : Bankruptcy prediction; Credit risk analysis; Abnormal credit risk behaviour; Gradient boosted decision trees; SHAP-values.; Konkurs förutsägelse; Kredit riskanalys; Abnomralt kreditbeteende; Gradient baserat beslutsträd; SHAP-värden.;

   Abstract : The field of bankruptcy prediction has experienced a notable increase of interest in recent years. Machine Learning (ML) models have been an essential component of developing more sophisticated models. Previous studies within bankruptcy prediction have not evaluated how well ML techniques adopt for data sets of companies with higher credit risks. READ MORE

4. 3. Risk Evaluation in a ML-Approximated Portfolio Environment

   University essay from KTH/Matematik (Avd.)

   Author : Filip Franzén; Karl Axel Nord; [2022]
   Keywords : Financial risk management; forecasting; machine learning; FMCG; Finansiell riskhantering; prognostisering; maskininlärning; konsumtionsvaror;

   Abstract : This thesis explores and evaluates the forecasting application of the machine learning method Gradient Boosting Decision Trees. This method is used to forecast the demand of the online grocery market with a 7-day time horizon. The thesis was conducted in collaboration with the online grocery company Mathem. READ MORE

5. 4. Prediction of Short-term Default Probability of Credit Card Invoices Using Behavioural Data

   University essay from KTH/Matematisk statistik

   Author : Billy Lu; [2022]
   Keywords : Probability of Default; Credit Risk; Short-term Default Prediction; Machine Learning; Gradient Boosting; Thresholding; Sannolikheten för Fallissemang; Kreditrisk; Kortsiktig Fallissemang Prediktion; Maskininlärning; Gradientförstärkning; Tröskling;

   Abstract : Probability of Default (PD) is a standard metric to model and monitor credit risk, a major risk facing financial institutions. Traditional PD models are used to forecast risk levels in the long-term, while short-term PD predictions are rarer, but they can support management decisions on an operational level. READ MORE

6. 5. Friends character classification personality quiz

   University essay from Uppsala universitet/Avdelningen för systemteknik

   Author : Ruben Hedström; Leon Lovén; Simon Mojtahedi; Fredrik Malmström; [2021]
   Keywords : Quiz; Friends; Machine learning; Information technology;

   Abstract : The purpose of this project was to create a personality quiz based on the scientifical method and machine learning that determine which character in the TV-series Friends that the person taking the quiz is the most similar to. The manuscripts from all the episodes were used to extract features and create a split training/test dataset. READ MORE