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> We scrape the data from the public GitHub source code to generate a model that stores prop type names and the type in which they have been set. Once we have a
by throwaway2016a 9y ago
> We scrape the data from the public GitHub source code to generate a model that stores prop type names and the type in which they have been set. Once we have a huge set of sample data we then feed this into AWS Machine Learning as a multi-class classification model.
I would literally pay for a tutorial on how that is done (not the scraping github part... that part seems straight forward)... the ML part.
Anyone know of a tutorial on how to build classification models like that?
- hakanito 9y agoMany classification models are available as open source. I'd start by downloading Weka [0] and play around with the different algos they have and feed in some training data, csv or similar. When you find a model with a good result (for example, look at the confusion matrix) you can try to find an open source implementation of that model in your favorite language and take it from there. [0] http://www.cs.waikato.ac.nz/ml/weka/ http://www.cs.waikato.ac.nz/ml/weka/