You are provided a large dataset of prior credit card transa…

Yоu аre prоvided а lаrge dataset оf prior credit card transactions containing the transaction amount, location, purchase time and average daily balance for the customer along with a known outcome of whether the purchase was eventually deemed as fraudulent (Yes or No).  Your company would like you to create a machine learning model that would predict the probability of an incoming transaction as potentially fraudulent. If the model shows promise, then it would be used in a real-time system and would need to make its prediction in less than 1 second of processing time. You have a choice between creating a model using k-NN or using the Decision Tree algorithm.  Answer both questions: Which algorithm do you think would make the better choice? Why do you reach this conclusion?