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Monotonic variables for GBM #14868
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Mark Landry commented: At first read, this looks like ordered factors. But this is modeling behavior. And it is subtly quite complex. It likely changes the way the entire algorithm operates to where we'd have to implement the basic tree split differently. They want a suboptimal model that fits the supposed natural order of the data sets they have. |
Alon Gilmore commented: Insurance and banking companies sometimes have very large multi-dimensional rating factors table that needs to be optimized. |
Jenna Yang commented: This feature has already been implemented in xgboost: Not only will it alleviate overfitting but also helps to eliminate relationships that do not make sense. |
Patrick Hall commented: See: https://0xdata.atlassian.net/browse/PUBDEV-3920 |
Javier Recasens commented: Will it be implemented for H2O gbm? This is currently implemented in the standard gmb R package via var.monotone argument. |
Michal Kurka commented: [~accountid:5b16f0d47dab4c51f61b5513], yes - good news is will be adding this feature in one of the future releases (1-2 months from now) |
JIRA Issue Migration Info Jira Issue: PUBDEV-1984 |
Monotonic variables for GBM
The ability to designate a variable as monotonically increasing or decreasing. This means that splits will only be chosen if the prediction for the left side is smaller (or larger, resp.) than the right.
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