resampling-p2p-lending

Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Imbalanced Learning Techniques

This repository contains all scripts used in the experiments of this work. The Python version was 3.6 and the base frameworks used for machine learning tasks and resampling were

Also, two classes were build in order to deal with cross validation in the presence of resampling: imbalance.crossValidationStratified and imbalance.classifyCrossValidation. This experiment was divided into two parts: preparation of the data and, finally, classification.

The sections below discuss each of these parts, detailing the data preparation and experiments scripts.

Data Preparation

The data set preparation script receives as input a series of CSV files obtained from the Lending Club. This script contains the following steps:

Data load and header sanity check
Data filter (charged off and fully paid) and concatenation
Removal of features to avoid data leakage
Removal and treatment of string variables
Removal of instances (loan requests) with many missing values
Removal of features (attributes) with many missing values
Removal of variables of low variability
Missing values imputation

Experiment Scripts

In the experiments, the major techniques to handle class imbalance were used. Each one of this techniques have a specific script.

baseline_p2p.py

This script calculates the baseline for the experiments. At first, the test and train data sets are defined, followed by the classifiers. Then, for each classifier the train data set is used to find the best parameters, using 5 fold cross validation. The final step consists of test the tunnel trained classifier at the test set, using 5 fold cross validation. To run the script:

python3.6 baseline_p2p.py > log_baseline.log 2> error_baseline.log

ensembles_p2p.py

The ensemble script execute the same steps that the baseline script. To run the script:

python3.6 ensembles_p2p.py > log_baseline.log 2> error_baseline.log

sampling_p2p_1.py

To run the script:

python3.6 sampling_p2p_1.py > log_baseline.log 2> error_baseline.log

sampling_p2p_5.py