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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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How to calculate variable importance by sampling in a predictive model that can be anything:...

Apparently there is no answer with a theoretical basis, but there are some informal solutions of different kinds, as implemented in different software packages such as Caret for R, and Fastai for Pyto …
Geoffrey Anderson's user avatar
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1 answer
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How to calculate variable importance by sampling in a predictive model that can be anything:...

As a rough draft of a solution, I suppose it would be useful to shuffle one at a time, each of the columns of predictor variables, rerun predictions, then check the effect on the metric like MSE versu …
Geoffrey Anderson's user avatar
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what to do with really strong features in machine learning

Which one would you pick and when? Use your data and do it both ways. Keep the one that works better empirically. This is exactly what machine learning is about. This is the data driven way of …
Geoffrey Anderson's user avatar