nums.experimental.nums_xgb module

class nums.experimental.nums_xgb.NumsDMatrix(X, y)[source]: Bases: xgboost.core.DMatrix

class nums.experimental.nums_xgb.RabitContext(actor_id, args)[source]

Bases: object

Context to connect a worker to a rabit tracker

class nums.experimental.nums_xgb.XGBClassifier(n_estimators=100, max_depth=6, learning_rate=0.3, tree_method='approx', objective='binary:logistic', booster='gbtree')[source]

Bases: object

fit(X, y)[source]

predict(X)[source]

nums.experimental.nums_xgb.train(params, data, *args, evals=(), **kwargs)[source]

nums.experimental.nums_xgb.xgb_predict_remote(result, X)[source]

nums.experimental.nums_xgb.xgb_train_remote(X, y, rabit_args, params, args, kwargs, *evals_flat)[source]