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I have a dataset of two identified populations that contains various parameters for each data point. I would like to find the best criterion, i.e. the relation between e.g. three of those parameters, that best separates those two populations.

Imagine for example that we look at the human population and we would like to find the best relation between parameters such as hight, age and weight to separate men from women.

I would like to do this in Python, but I don't know the correct keywords. I'm pretty sure this is a common optimization problem, so there likely already exists a library out there that can do it.

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One option is a decision tree.

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You could also try a linear SVM and examine the weights. Sort the features by resulting weights to get a view of which ones are more important.

Or, just run a statistical logistic regression model and produce p-values for each feature. A quick search shows that the statsmodel package will do this for you.

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