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I need to analyse a data set of around 30,000 properties listed or sold over 2 years

The main aim is to: Minimize risk and boost profit investments in a short-term market and a long-term strategy. What possible data mining models and solutions could be used to analyse this data and achieve the aim?

I was thinking possibly finding price correlations between house location, number of rooms, land size and price and finding the average price to then look for lower price options to invest.

The Data includes:

Address.

Number of Rooms. Price

Type of property

Postcode

Date Sold.


Distance: Distance from CBD in Kilometres.


General Region

Number of Properties that Exist in the Suburb.

Number of Rooms

Number of Bathrooms.


Number of Car Spots.

Land Size in Square Metres.

Building Size in Square Metres.

Year the House was Built.


Governing Council for the Area.

Latitude: Latitude of the Property.

Longitude: Longitude of the Property.

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  • 1
    $\begingroup$ There is no one model that you can immediately say will perform the best on your specific dataset. This is part of the fun of ML, trying out a bunch of different models to see which works the best. $\endgroup$ – Ethan Mar 19 at 0:14

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