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Category: Feature Engineering

Building an F1 prediction engine – Feature Engineering Part V

Building an F1 prediction engine – Feature Engineering Part V

Up till now we have discussed on how we can create some features and how we can encode them. We’ve, hopefully, ended up with lots of variables and we are seeking a way to keep the top-performing ones. In this post I’m going to explain ‘why’ and ‘how’ we should cleverly select our features. Please…

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Building an F1 prediction engine – Feature Engineering Part III

Building an F1 prediction engine – Feature Engineering Part III

After creating all features, it is quickly evident that there are a lot of missing data. Missing data should be dealt with before going on to the next phases of our model building. In this post, I’m going to quickly describe the reasons behind the missing values and ways to treat them. Please share the…

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Building an F1 prediction engine – Feature Engineering Part II

Building an F1 prediction engine – Feature Engineering Part II

Having explored the data, checked what is available and what’s not, found any inconsistencies and potential problems, it is time to get creative. Feature extraction is the step where an experienced data scientist can really make the difference and improve the subsequent model’s accuracy; many times more than it will be possible through algorithm selection…

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