比如说,如果我们有1000个样本,其中300个正样本,700个负样本,则base_score就是0.3。 4. seed/random_state : 随机数种子 xgb.train():seed xgb.XGBRegressor() :random_state 5. missing : 缺失值的处理(填充方式)。XGBoost默认会将所有的空值当作稀疏矩阵中的0来进行处理 6. importance_type 是否输出特征的...
它可能是有用的,例如,建模总损失的保险,或任何结果,可能是 Tweedie 分布。 base_score [default=0.5] 所有实例的初始预测得分,全局偏置 对于足够多的迭代,更改此值不会产生太大影响。 eval_metric 验证数据的评估指标,将根据目标(回归的 rmse,分类的损失,排名的平均精度)分配缺省指标 用户可以添加多个评估指标。Py...
因此,当调用booster.save_model(在R中是xgb.save)时,XGBoost会保存树、一些模型参数(例如在训练树中的输入列数)以及目标函数,这些组合在一起代表了XGBoost中的“模型”概念。至于为什么将目标函数保存为模型的一部分,原因是目标函数控制全局偏差的转换(在XGBoost中称为base_score)。用户可以与他人共享此模型,用于预测...
silent=True,objective='reg:linear',booster='gbtree',n_jobs=1,nthread=None,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,random_state=0,seed=None,missing=None,importance_type='...
base_score [ default=0.5 ] eval_metric [ default according to objective ] evaluation metrics for validation data, a default metric will be assigned according to objective( rmse for regression, and error for classification, mean average precision for ranking ) ...
XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1, importance_type='gain', interaction_constraints='', learning_rate=0.300000012, max_delta_step=0, max_depth=6, min_child_weight=1, missing=nan, monotone_const...
XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=None, n_estimators=100, n_jobs=1, nthread=None, ...
base_score: The initial prediction score of all instances, global bias. seed : int Random number seed. (Deprecated, please use random_state) random_state : int Random number seed. (replaces seed) missing : float, optional Value in the data which needs to be present as a missing value. ...
base_score: –The initial prediction score of all instances, global bias.初始实例分数 seed: 参数类型(int)– Random number seed. (Deprecated, please use random_state).随机种子 random_state: 参数类型(int)– Random number seed. (replaces seed).随机种子 missing: 参数类型(float, optional)– Valu...
class xgboost.XGBRegressor(max_depth=3, learning_rate=0.1, n_estimators=100, silent=True, objective='reg:linear', booster='gbtree', n_jobs=1, nthread=None, gamma=0, min_child_weight=1, max_delta_step=0 max_depth: 参数类型() – Maximum tree depth for base learners. 树的最⼤...