Melbourne Property Price Prediction

Introduction

In this assignment, we are going to try to build and merge some different ML models to predict the price of property in melb according to their features. Besides, UI is another part of this project for the service to users. Hence, user are able to get price prediction after loading the information of property.

Tasks

• Dataset Collection: Xavier Yan
• Machine Learning: Pengcheng Xie, ChengQiang Qin, Hanming Yin,
• UI & Authorization: Xavier Yan, Zeyu Zhang
• Git Repo Control: Hanming Yin

Frame

• RawData
• DataCleaning
• FeatureEngineering
• ModelsTrainning
• ModelsBagging
• Web
• Auth
• Demo
• GuidesOfGit.md
• README.md

RawData

Dataset from Melbourne House Market in kaggle.

DataCleaning

• Drop Invalid Data
• Fill Missing Data By Median or Average

FeatureEngineering

Data processing and feature augmentation

ModelsTrainning

Building multiple models

ModelsBagging

Merging models

Web

Human-computer interface

Communication Chanel

• mobile app Wechat in English
• comments on github

Repo

COMP9321 Ass3

Manual

cd 8.Demo
python3 myProperty.py