The following example shows multi model cross validation using td_lightgbm.
The argument return_cvbooster is not supported yet for cv().
>>> opt_cv_m = td_lightgbm.cv(params={}, train_set=obj_m_v, num_boost_round=30) >>> opt_cv_m partition_column_1 partition_column_2 model console_output 0 1 11 {'l2-mean': [0.2228372778767334, 0.20378581597... [LightGBM] [Warning] Auto-choosing col-wise mu... 1 0 11 {'l2-mean': [0.22670871234512563, 0.2076397899... [LightGBM] [Warning] Auto-choosing col-wise mu... 2 1 10 {'l2-mean': [0.2254886102590233, 0.20486831815... [LightGBM] [Warning] Auto-choosing col-wise mu... 3 0 10 {'l2-mean': [0.22325269845549206, 0.2001155354... [LightGBM] [Warning] Auto-choosing col-wise mu...