I. prepare a breast cancer data set that is provided by python datasets package. you may split this dataset into training set and testing set according to your own splitting ratio. the following picture is a code example how to load the cancer dataset into your python file. you can print(data. data) and print(data. target) to preview the features and labels you can also print(data) to preview the whole dataset. ii. use the gaussiannb to train naïve bayes classifier with the training set and then test this model with your testing set. iii. use classification_report library to draw a short report in python

Many prestigious universities have a system called a “legacy preference system” which is used to decide which applicants should be accepted to the university. if an applicant’s parent is an alumnus of the university, the applicant will be admitted with lower gpa and sat scores than if the parent is not an alumnus. (there is currently a lot of discussion about the fairness of this system, but universities get a lot of money from their alumni so they are unwilling to change ) your assignment for mp2 is to implement a computerized system like this for a very small prestigious university. the university has two schools, liberal arts and music, each with their own criteria for accepting students. your program must read in certain information about an applicant and print a message saying whether the applicant should be accepted or not.