MultilayerCreditScoring
This repository includes a python script that implements the MultilayerCreditScoring (MCS) algorithim presented in the paper Evolution of Credit Risk Using a Personalized Pagerank Algorithm for Multilayer Networks.
Usage instructions
What is supported regarding the format of the input data:
to be continued...
Usage and the parameters the user can control
- Filename for input data
- Network_type, defaUlt is bipartite multilayer but mulitplex can also be specified !?! //TODO: check this further
- Alpha parameter for the personalized pagerank algorithm. Default is 0.85
We will do a MCS class that takes all the neccassary parameters in its contructor and it will run the caluclatinson directly afterwards. Then the user can query the results he is interesed in by examaning the relevant properites of the MCS object.
Release files for multilayer-credit-scoring 0.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| multilayer-credit-scoring-0.0.7.tar.gz | 4.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| multilayer_credit_scoring-0.0.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.3 kB
Release files / multilayer-credit-scoring-0.0.7.tar.gz
| Download URL | multilayer-credit-scoring-0.0.7.tar.gz |
|---|---|
| Size | 4.9 kB |
| Tags | Source |
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Release files / multilayer_credit_scoring-0.0.7-py3-none-any.whl
| Download URL | multilayer_credit_scoring-0.0.7-py3-none-any.whl |
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| Size | 18.3 kB |
| Tags | Python 3 |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.4
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