In the PC industry, there are different computer setups for omnifarious PC users. Different types of customers have different needs and budget for their computers. For instance, we think that gamers prefer desktops or laptops with high-end GPU and CPU while office users prefer the ones with decent CPU and long battery life. Hence, being aware of the different needs from different customers could help computer retailers dramatically with marketing and resource allocation. With this background, we decided to build a machine learning model that can predict a users’ persona based on the information of their computers.
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Clone this repository.
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On the command line, navigate to this repository locally.
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on the command line, use
python run.py test runs the pipeline with the test-project target. This will run the test build classifier. THIS PROCESS WOULD LAST HOURS!!!
python run.py build-classifier to build all classifier. THIS PROCESS WOULD LAST HOURS!!!
python run.py hypo-test to run the hypothesis test on column 'ram' with other columns.
python run.py chi-square-test to run the hypothesis test on column 'ram' with other columns.