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We should have a testing framework / experimentation engine to test the algorithms for robustness to various types of input data (normalized / not-normalized / bad condition numbers / partial separability / low class sizes, etc.) -- eventually we might even want some sort of switching method that, for example, might detect bad conditioning in Newton's method and switch to gradient descent. This will require first writing a way to generate such data.
We should have a testing framework / experimentation engine to test the algorithms for robustness to various types of input data (normalized / not-normalized / bad condition numbers / partial separability / low class sizes, etc.) -- eventually we might even want some sort of switching method that, for example, might detect bad conditioning in Newton's method and switch to gradient descent. This will require first writing a way to generate such data.
@mcg1969 @jcrist
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