working: Dataset Full database Non functional gui functional gui Database connected to application Fully functional application.
HOUSING PRICE PREDICTION
working:
“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”.
you can check your property prices through this application.
Laptop
modem
Application
softwares
tools
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Laptop | Equipment | 2 | 50 | 100 |
| Total in (Rs) | 100 |
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