Decided to try to apply the data mining techniques learnt from Intelligent systems course on publicly available economic data. The two sources for data that I will start of with are:

I will run a mix of supervised and unsupervised techniques. When conducting supervised analysis I will look for relationships between economic indications to provide inference on discussion topics such as:

  • The value of high equality in an economy
  • Benefits of non-livestock or livestock agriculture
  • Gains through geographic decentralization of population
  • Estimates on sustainable housing price ranges
  • The value of debt
  • Productivity of information technology
  • Cost and benefits of lax/tight immigration policies
  • Cost and benefits free-market/regulated/centralized economic governance

Techniques used for quantitative analysis will be varied a dependent on subsequent success. To start with I plan on using the raw data sources in conjunction with some simplistic python and Java scripts. If that turns out to be ineffective I will work with MatLab, Weka and Netica. Google and the World Bank also have numerous interfaces for exploring data. This will be an ongoing project so I will make these posts help myself keep track of progress.

 

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