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Is there a connection between the coefficients of linear regression and the correlation of individual features with the resulting one?
Suppose we have m dimensions of the form (x1,...xn), all xi -numbers, and m values of the resulting feature yi.
Let's bring all xi to the range [0,1] and calculate the feature coefficients for linear regression.
Is it true that the feature with the highest coefficient in the linear model will have the highest correlation with the resulting feature, and the one with the minimum coefficient will have the lowest correlation?
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