Built-in R2 (R-squared) metric

[jameslamb]

Description

LightGBM should add a built-in R^2 metric.

Benefits of this work

• prevents the need to implement this metric in a custom function (as seen in [CUDA] [python-package] Regarding the time consumption of training LightGBM with CUDA #6982, for example)

Acceptance criteria

• LightGBM supports an r2 metric (on both CPU and GPU)

Approach

Do something like this to find where rmse shows up:

git grep -i rmse

And follow that as a guide for what to update.

At a minimum:

• https://github.com/microsoft/LightGBM/blob/master/src/metric/regression_metric.hpp
• https://github.com/microsoft/LightGBM/blob/master/src/metric/cuda/cuda_regression_metric.cpp

• LightGBM/include/LightGBM/config.h

  Line 1013 in 27dcf82

  // desc = metric(s) to be evaluated on the evaluation set(s)

• LightGBM/R-package/R/metrics.R

  Line 9 in 27dcf82

  .METRICS_HIGHER_BETTER <- function() {

Notes

This should be the standard R^2, not the "adjusted" R^2 which penalizes models with more features.

See https://en.wikipedia.org/wiki/Coefficient_of_determination

[jameslamb]

I've added this to #2302 along with other feature requests.

Adding the awaiting response label so it'll automatically be closed after 30 days without any comments. Anyone finding this is welcome to implement it... just leave a comment saying you'd like to work on it.

[nicklamiller]

Hi @jameslamb, I'd like to work on this issue, I've done a little preliminary work so should have a PR open soon-ish.