CSE5ML: Machine Learning - SVM, Linear Regression and K-Nearest Neighbor - IT Assignment Help

Assignment Task:

Overview

• This assignment contributes 20% of your final mark in the subject. Please read this sheet carefully before doing your assignment.    

• The assignment aims to consolidate your knowledge on Regression models and develop your Machine Learning skills. 
 
Policies

• This is an individual assignment.

• Plagiarism is the submission of somebody else’s work in a manner that gives the impression that the work is your own. The Department of Computer Science and Information Technology at La Trobe University treats plagiarism very seriously. When it is detected, penalties are strictly imposed.

Problem Description

The assignment requires you to develop 3 end to end regression models: SVM, Linear Regression and K-Nearest Neighbors (all have been studied during the course both in lectures and labs). The models should be developed to accurately predict median value of Boston houses in any given suburb, where the suburbs are described based on their provided characteristics: 
 o CRIM     per capita crime rate by town

o ZN  proportion of residential land zoned for lots over 25,000 sq.ft.

o INDUS    proportion of non-retail business acres per town

o CHAS     Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)

o NOX      nitric oxides concentration (parts per 10 million)

o RM       average number of rooms per dwelling

o AGE      proportion of owner-occupied units built prior to 1940

o DIS      weighted distances to five Boston employment centres

o RAD      index of accessibility to radial highways

o TAX      full-value property-tax rate per $10,000

o PTRATIO  pupil-teacher ratio by town

o B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town

o LSTAT    % lower status of the population

o MEDV     Median value of owner-occupied homes in $1000's

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