multi-classification using Xgboost Scikit API

Question

I am confused with how and where to set num_class parameter for multi-classification using Xgboost Scikit API. On the scikit website, there is no such parameter in docs.

xgboost.XGBClassifier(max_depth=3, learning_rate=0.1, n_estimators=100,
    silent=True, objective='binary:logistic', nthread=-1, gamma=0,
    min_child_weight=1, max_delta_step=0, subsample=1, colsample_bytree=1,
    colsample_bylevel=1, reg_alpha=0, reg_lambda=1, scale_pos_weight=1,
    base_score=0.5, seed=0, missing=None)

Possible duplicate of multiclass classification in xgboost (python) — kostek

epattaro epattaro · Accepted Answer · 2017-03-13T17:38:51

The XGB Classifier wrapper function does not require for you to specify the amount of classes priorly. The "label" column passed on the fit is used to specify how many/which classes you will be working with.

multi-classification using Xgboost Scikit API

1 Answers