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I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/factors that contribute the highest towards the academic performance of the students. Which machine learning algorithm is the most suitable for this task?

A friend suggested using clustering algorithm that can segment the students into different performance groups, but I think that will not solve my problem.

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You’re looking for an algorithm with identifies the explained variance of each feature. The first to my mind was Principal Component Analysis. But the more I thought about it, I personally am more comfortable with decision trees and their interpretability will often give a similar insight.

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