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In this project we used Logistic regression to predict the case when a client will behave as a default one. Here we apply prepocessing techniques to the main dataframe and create diffent models concening the differences between characteristics in the dataset.

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PhyData/Bad_good_client_Project_Raul_and_Dario

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Bad and Good Client Project

In this project we used Logistic regression to predict the case when a client will behave as a default one. Here we apply prepocessing techniques to the main dataframe and create diffent models concening the differences between characteristics in the dataset.

The dataset can be easily loaded from the default_credit.csv file.

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Dr. Raúl Guerrero

Dr. Dario Lopez

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In this project we used Logistic regression to predict the case when a client will behave as a default one. Here we apply prepocessing techniques to the main dataframe and create diffent models concening the differences between characteristics in the dataset.

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