Essays about: "Gradient baserat beslutsträd"

Found 3 essays containing the words Gradient baserat beslutsträd.

  1. 1. 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

  3. 2. 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

  4. 3. Predicting Default Probability in Credit Risk using Machine Learning Algorithms

    University essay from KTH/Matematisk statistik

    Author : Sarah Kornfeld; [2020]
    Keywords : Credit risk; default probability; machine learning; logsitic regression; basel framework; Kreditrisk; fallissemangssannolikhet; maskininlärning; logistisk regression; baselregelverk;

    Abstract : This thesis has explored the field of internally developed models for measuring the probability of default (PD) in credit risk. As regulators put restrictions on modelling practices and inhibit the advance of risk measurement, the fields of data science and machine learning are advancing. READ MORE