In this example of classification problem, we will try to find the best model for our dataset to predict diabetes using machine learning in Python.

If you miss payments or you don't pay the right amount, your creditor may send you a default notice, also known as a notice of default. If the default is applied it'll be recorded in your credit file and can affect your credit rating. An account defaults when you break the terms of the credit agreement.

Built a classifier to predict whether a loan case will be paid off or not. Used classification algorithms (k-Nearest Neighbour, Decision Tree, Support Vector Machine, Logistic Regression). Each result is reported with the accuracy of each classifier (Jaccard index, F1-score, LogLoass)

build a classifier to predict whether a loan case will be paid off or not. in loan applications, clean the data, and apply different classification algorithm on the data. use the following algorithms to build your models: k-Nearest Neighbour Decision Tree Support Vector Machine Logistic Regression The results is reported as the accuracy of each …