Add to ORKGWhile there is a large literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in our country, where there is not much scientific work on this topic. Recognising who is becoming a bad debtor is not easy. There are several ways to analyse the data, which may even show different results. In this paper, my aim is to predict the default of household loans using logistic regression and neural networks. The question is, which method produces the better results
The article attempts to answer the question whether or not the latest bankruptcy prediction techniqu...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
In this thesis, alternative machine learning techniques have been used to test if these perform bett...
The prediction of corporate bankruptcies is an important and widely studied topic since it can have ...
This master thesis explore the potential of Machine Learning techniques in predicting default of veh...
Abstract Today, the intensity of industry competition has led many companies going bankrupt and pull...
The profitability of loan granting institutions depends largely on the institutions’ ability to accu...
This study contributes to the credit risk management literature by describing a new, user-friendly, ...
In the business environment, Least-Squares estimation has long been the principle statistical method...
We evaluate the prediction accuracy of models designed using different classification methods depend...
Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep ...
In business analytics and the financial world, bankruptcy prediction has been an interesting and wid...
Prediction of corporates bankruptcies is a topic that has gained more importance in the last two dec...
Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks ...
The scenario considered is that of a credit association, a bank or an- other nancial institution wh...
The article attempts to answer the question whether or not the latest bankruptcy prediction techniqu...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
In this thesis, alternative machine learning techniques have been used to test if these perform bett...
The prediction of corporate bankruptcies is an important and widely studied topic since it can have ...
This master thesis explore the potential of Machine Learning techniques in predicting default of veh...
Abstract Today, the intensity of industry competition has led many companies going bankrupt and pull...
The profitability of loan granting institutions depends largely on the institutions’ ability to accu...
This study contributes to the credit risk management literature by describing a new, user-friendly, ...
In the business environment, Least-Squares estimation has long been the principle statistical method...
We evaluate the prediction accuracy of models designed using different classification methods depend...
Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep ...
In business analytics and the financial world, bankruptcy prediction has been an interesting and wid...
Prediction of corporates bankruptcies is a topic that has gained more importance in the last two dec...
Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks ...
The scenario considered is that of a credit association, a bank or an- other nancial institution wh...
The article attempts to answer the question whether or not the latest bankruptcy prediction techniqu...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
In this thesis, alternative machine learning techniques have been used to test if these perform bett...