Credit Score Prediction

Abstract

Abstract: A credit score is the numerical representation of a person’s credit worthiness, which is the likelihood that they will replay the borrowed money. Credit scores are used by lenders, such as banks and credit companies, to evaluate the risk of lending money or extending credit to an individual. Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without being explicitly programmed. Learning algorithms in many applications that we make use of daily. These algorithms are used for various purposes like data mining, image processing, predictive analytics, etc. to name a few. The main advantage of using machine learning is that, once an algorithm learns what to do with data, it can do its work automatically. Various algorithms used in machine learning, along with their drawbacks and usages, have been discussed briefly. A model is also made using one of these algorithms which provide minimum error of provide correct predictions based on the previous data available. The model is made using random forest classifier algorithm which gave the highest accuracy ,out of all the machine learning algorithm, up to 79.97%. The result was printed at last containing the predictions made on the test data , id and customer id.