Attribute selection in h2o

时光总嘲笑我的痴心妄想 提交于 2019-12-06 05:15:54

No there are not currently feature selection functions in H2O -- my advice would be to use Lasso regression (in H2O this means use GLM with alpha = 1.0) to do the feature selection, or simply allow whatever machine learning algorithm (e.g. GBM) you are planning to use to use all the features (they'll tend to ignore the bad ones, but it could still degrade performance of the algorithm to have bad features in the training data).

If you'd like, you can make a feature request by filling out a ticket on the H2O-3 JIRA. This seems like a nice feature to have.

In my opinion, Yes

My way is use automl to train your data.

after training, you can get a lot of model.

use h2o.get_model method or H2O server page to watch some model you like.

you can get VARIABLE IMPORTANCES frame.

then pick your features.

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