Data Visualisation and Analytics Assignment 3

Department of Econometrics and Business Statistics, Monash University

Due Date: 24th October 2019 at 1PM

A Implementing kNN classification (10 Marks)

This part of the assignment involves kNN classification of a dataset of 140 bank customers and must be

completed by ALL students. Note that this assignment is based on simulated data and each student has

their own personalised dataset. You must enter your student ID number before downloading your unique

dataset. The data can be downloaded here.

In the dataset, for each employee, data were collected on the following variables:

• Name : Customer name.

• Default: Did customer fail to pay back loan (Default) or successfully pay back the loan (No Default).

• WeeklyIncome : Income per week.

• EmploymentDuration : Time spent in current job.

• WeeklySpend : Average amount of money spent per week.

• Children : Number of children.

• Age : Customers age.

• Sample : Whether the customer is in the training sample or test sample.

The objective is to predict on the basis of Weekly Income, Employment Duration, Weekly Spend, Number of

Children and Age whether a customer will default. The training sample can be used for determining a rule

for prediction and the test sample for evaluation. You may assume that the costs of both types of incorrect

prediction are equal. All numerical variables have been standardised by subtracting the mean and dividing

by the standard deviation of the traning sample. You do NOT need to standardise the data.

Analytics留学生作业代做

Once you have downloaded your data, complete the assignment by g