Characterizing model performance using global and local feature contributions

A method, comprising:

• obtaining a set of coefficients from a linear model that uses a set of features inputted into a statistical model to estimate an output of the statistical model;
• combining, by one or more computer systems, the set of coefficients with a set of feature values of the features to calculate a set of local contributions of the features toward the output of the statistical model, wherein each local contribution in the set of local contribution is calculated by multiplying each feature value in the set of feature values by a coefficient for a corresponding feature in the linear model;
• and
• outputting, based on a first ranking of the set of features by the set of local contributions, a first subset of the features for use in characterizing a local performance of the statistical model.

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

• obtaining a set of coefficients from a linear model that uses a set of features inputted into a statistical model to estimate an output of the statistical model;
• combining the set of coefficients with a set of feature values of the features to calculate a set of local contributions of the features toward the output of the statistical model, wherein each local contribution in the set of local contribution is calculated by multiplying each feature value in the set of feature values by a coefficient for a corresponding feature in the linear model;
• and
• outputting, based on a first ranking of the set of features by the set of local contributions, a first subset of the features for use in characterizing a local performance of the statistical model.