![]() ![]() Fritsch.įirst let load the package and an example dataset. If you’re unsure on what a neural network exactly is, I find this a good place to start.įor this example the R package neuralnet is used, for a more in-depth view on the exact workings of the package see neuralnet: Training of Neural Networks by F. The actual procedure of building a credit scoring system is much more complex and the resulting model will most likely not consist of solely or even a neural network. The following is an strongly simplified example. Neural networks are situated in the domain of machine learining. A creditscoring system can be represented by linear regression, logistic regression, machine learning or a combination of these. In other words: creditworthiness=f(income, age, gender, …). income, age, gender) that lead to a given level of creditworthiness. In the end it basically comes down to first selecting the correct independent variables (e.g. ![]() ![]() One can take numerous approaches on analysing this creditworthiness. Credit scoring is the practice of analysing a persons background and credit application in order to assess the creditworthiness of the person. ![]()
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February 2023
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