HOUSING PRICE PREDICTION

Project Title

HOUSING PRICE PREDICTION

Project Area of Specialization Computer ScienceProject Summary making an application which can predict house prices through different parameter and generate graph to show price differences. required: -dataset _database _api  _gui  Tools: machine learning and data mining 

working:

• Dataset
• Full database
• Non functional gui
• functional gui
• Database connected to application
• Fully functional application.

Project Objectives

“Housing Price in Beijing” is a dataset containing more than 300, 000 data with 26 variables representing housing prices traded between 2009 and 2018. These variables, which served as features

 of the dataset, were then used to predict the average price per square meter of each house. The next

Step was to investigate missing data. Variables with more than 50% missing data would be removed

From the dataset. The variable “Day on market” was removed because of 157, 977 missing data. Any

Observation which had missing values were also removed from the dataset. Below are a few feature

 engineering processes which were done to cleanse the dataset: • Remove attributes indicating the

Number of kitchens, bathrooms, and drawing rooms due to their ambiguity. • Set the number of living

Rooms (bedrooms were mistranslated to living rooms) in a range from 1 to 4. • Add attribute

“Distance” indicating the distance of the house from the center of Beijing. • Replace attribute

“construction Time” with attribute “age” by deducting the year that the house constructed from the

Current year (2019). • Set minimum values for attributes “price” and “area”. • Split the attribute “floor”

into attributes “floor Type” and “floor Height”.

Project Implementation Method

• Dataset
• Full database
• Non functional gui

Benefits of the Project

you can check your property prices through this application.

Technical Details of Final Deliverable

Laptop

modem

Application 

softwares

tools

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Others Core Technology Big DataOther Technologies Internet of Things (IoT)Sustainable Development Goals No Poverty, Good Health and Well-Being for People, Quality Education, Gender Equality, Clean Water and SanitationRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	100
Laptop	Equipment	2	50	100