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Google Cloud Certified Professional Data Engineer · Google Cloud
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I think the best option is B. D could be an option but what if the feature is very correlated to the result ?
B: combine the dependent features. It is more like PCA (principal component analysis). D: could be the answer, but what if that feature is very important, or how often do you get a feature with more than 50% NULL values?
I am not into ML, to be honest, so I will rely on community opinion and choose B