How to determine which features matter the most?
One common approach is to use Principal Component Analysis (PCA) and drop the directions with less variance. See here for instance:
Using principal component analysis (PCA) for feature selection

The latest version of sklearn allows to estimate the feature importance for any estimator using the so-called permutation importance:
Permutation feature importance
Random forest in sklearn also have other methods implemented to estimate the feature relevance:
Feature importances with a forest of trees