> you can look at magnitude and direction of various coefficients and conclude certain obvious things. Sometimes, but if you have correlated predictors, the 'e

> you can look at magnitude and direction of various coefficients and conclude certain obvious things. Sometimes, but if you have correlated predictors, the 'explainability' can be distributed across coefficients of those predictors in unpredictable ways. Training a linear model twice with two different subsets of training data can give you very different coefficient weights.