When it comes to trees, the API for handling categoricals is simpler than
the implementation. Traditionally, tree-based models' handling of
categorical variables differs from both ordinal and one-hot encoding, while
both of those will work reasonably well for many problems. We are working
on
That's an excellent discussion! I've always wondered how other tools like R
handled naturally categorical variables or not. LightGBM has a scikit-learn
API which handles categorical features by inputting their columns names (or
indexes):
```
import lightgbm
lgb=lightgbm.LGBMClassifier()
Thanks to all our 200+ contributors, we are announcing a release candidate
for the upcoming release.
On top of a few exciting features, we're also deprecating positional
arguments in
many places where the constructor/method accepts many arguments.
for example, SVC(.5, "poly") will need to be
