Machine Learning predicts the likelihood of debt repayment

In 2014, the Data Analysis and Machine Learning Contest organizer Kaggle announced a contest to predict a loan applicant’s repayment based on their background information. Imperial College London hosted the competition and offered a large chart of anonymized financial data about the loan applications, applicants and their loan installments.

The aim of the competition was to create a program that would be best able to predict the applicant’s loan repayment based on his background information. A table of anonymized, unlabeled background information was made available to list details of all the repayments. In addition to the anonymization, data titles were omitted, so each column in the table listed information about some unstated variable of unknown purpose.

Continue reading “Machine Learning predicts the likelihood of debt repayment”