Imagine A bank manager is given a data set containing records of 1000 applicants who have
applied for a loan. The bank manager uses a suitable machine learning model to categorize the
records of applicants into two classes either approved or disapproved. He discovered that, when
other similar datasets are used, it fails to predict whether an application of a loan seeker is approved
or not. Depending on this scenario, answer the following questions.
a) In the above scenario the machine learning algorithm belongs to which category? (Hint.
Classification)
b) Identify the reasons of two different natures of the model towards similar datasets and
explain the problem. (Hint. Overfitting. Draw the graph)
c) Solve the above problem with necessary mathematical model. (Hint. Regularization)