sentiment_xgboost.py 文件源码

def train(params, dmatrix_train, dmatrix_validate):
    params['silent'] = 1
    params['objective'] = 'binary:logistic'  # output probabilities
    params['eval_metric'] = 'auc'

    num_rounds = params["num_rounds"]
    early_stopping_rounds = params["early_stop_rounds"]

    # early stop will check on the last dataset
    watchlist = [(dmatrix_train, 'train'), (dmatrix_validate, 'validate')]
    bst = xgb.train(param, dmatrix_train, num_rounds, watchlist, early_stopping_rounds=early_stopping_rounds)

    print "parameters: {}".format(param)
    print "best {}: {:.2f}".format(param["eval_metric"], bst.best_score)
    print "best_iteration: %d" % (bst.best_iteration)

    return params,bst