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Data Mining in Practice: Analysing Real Estate


Relational Data Mining without ILPBig data and data mining for CRM?Data mining- Clustering techniquesReference about social network data-miningPreprocessing in Data mining?City pollution data for data mining projectAre there any programmers who might find programmable heuristics useful?How's frequent pattern mining in data mining?Classification methods using one overlapping featureStatistical analysis vs Data mining













0












$begingroup$


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.










share|improve this question







New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$







  • 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
    2 days ago















0












$begingroup$


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.










share|improve this question







New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$







  • 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
    2 days ago













0












0








0





$begingroup$


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.










share|improve this question







New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




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.







data-mining bigdata






share|improve this question







New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question







New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




share|improve this question






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Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked Mar 18 at 22:08









JavasaurusrexJavasaurusrex

1




1




New contributor




Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Javasaurusrex is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







  • 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
    2 days ago












  • 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
    2 days ago







1




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
2 days ago




$begingroup$
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
2 days ago










0






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