Mining the Polish Bankruptcy Data
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Updated
Dec 24, 2020 - Jupyter Notebook
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polish-bankruptcy-data
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Updated
Jan 13, 2019 - Jupyter Notebook
Analyzed 64 financial ratios of 6 thousand companies that went bankrupt and built a Logistic Regression classification model to predict bankruptcy. Feature selection is performed with Simulated Annealing to extract the optimal subset of features that maximizes Accuracy rate.
feature-selection
logistic-regression
simulated-annealing
smote
classification-model
polish-bankruptcy-data
metaheuristic-optimisation
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Updated
Dec 26, 2020 - Jupyter Notebook
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