在 MacOS(Monterey,Apple M1)上使用 H2O(来自 Python 3.9.10)和 XGBoost 后端时出错
Error using H2O (from Python 3.9.10) and XGBoost backend on MacOS (Monterey, Apple M1)
我目前正在尝试使用来自 Python 的 H2O,但我在 Mac OS 上遇到了一些问题与 XGBoost。
好像哪里都找不到H2O
更准确地说,下一个简单的片段
import pandas as pd
import h2o
data = [['2015-01-01', '2490.925806' , '-0.41'],
['2015-01-02', '2412.623113' , '-0.48'],
['2015-01-03', '2365.611276' , '-0.55']]
df = pd.DataFrame(data, columns=["time", "base", "target"]).set_index("time", drop=True)
h2o.init(nthreads=-1)
estimator = h2o.estimators.H2OXGBoostEstimator()
training_frame = h2o.H2OFrame(df)
estimator.train(["base"], "target", training_frame)
给我错误:
H2OResponseError: Server error water.exceptions.H2ONotFoundArgumentException:
Error: POST /3/ModelBuilders/xgboost not found
Request: POST /3/ModelBuilders/xgboost
data: {'training_frame': 'Key_Frame__upload_893634781f588299bbd20d51c98d43a9.hex', 'nfolds': '0', 'keep_cross_validation_models': 'True', 'keep_cross_validation_predictions': 'False', 'keep_cross_validation_fold_assignment': 'False', 'score_each_iteration': 'False', 'fold_assignment': 'auto', 'response_column': 'target', 'ignore_const_cols': 'True', 'stopping_rounds': '0', 'stopping_metric': 'auto', 'stopping_tolerance': '0.001', 'max_runtime_secs': '0.0', 'seed': '-1', 'distribution': 'auto', 'tweedie_power': '1.5', 'categorical_encoding': 'auto', 'quiet_mode': 'True', 'ntrees': '50', 'max_depth': '6', 'min_rows': '1.0', 'min_child_weight': '1.0', 'learn_rate': '0.3', 'eta': '0.3', 'sample_rate': '1.0', 'subsample': '1.0', 'col_sample_rate': '1.0', 'colsample_bylevel': '1.0', 'col_sample_rate_per_tree': '1.0', 'colsample_bytree': '1.0', 'colsample_bynode': '1.0', 'max_abs_leafnode_pred': '0.0', 'max_delta_step': '0.0', 'score_tree_interval': '0', 'min_split_improvement': '0.0', 'gamma': '0.0', 'nthread': '-1', 'build_tree_one_node': 'False', 'calibrate_model': 'False', 'max_bins': '256', 'max_leaves': '0', 'sample_type': 'uniform', 'normalize_type': 'tree', 'rate_drop': '0.0', 'one_drop': 'False', 'skip_drop': '0.0', 'tree_method': 'auto', 'grow_policy': 'depthwise', 'booster': 'gbtree', 'reg_lambda': '1.0', 'reg_alpha': '0.0', 'dmatrix_type': 'auto', 'backend': 'auto', 'gainslift_bins': '-1', 'auc_type': 'auto', 'scale_pos_weight': '1.0'}
有关我的发行版的更多信息:
- OS:蒙特雷 12.3
- 处理器:Apple M1
- Python: 3.9.10
- H2O: 3.36.0.3
我怀疑 Apple M1 是错误的原因,但事实真的如此吗?
抱歉,Apple M1 处理器尚不支持 XGBoost。
我目前正在尝试使用来自 Python 的 H2O,但我在 Mac OS 上遇到了一些问题与 XGBoost。 好像哪里都找不到H2O
更准确地说,下一个简单的片段
import pandas as pd
import h2o
data = [['2015-01-01', '2490.925806' , '-0.41'],
['2015-01-02', '2412.623113' , '-0.48'],
['2015-01-03', '2365.611276' , '-0.55']]
df = pd.DataFrame(data, columns=["time", "base", "target"]).set_index("time", drop=True)
h2o.init(nthreads=-1)
estimator = h2o.estimators.H2OXGBoostEstimator()
training_frame = h2o.H2OFrame(df)
estimator.train(["base"], "target", training_frame)
给我错误:
H2OResponseError: Server error water.exceptions.H2ONotFoundArgumentException:
Error: POST /3/ModelBuilders/xgboost not found
Request: POST /3/ModelBuilders/xgboost
data: {'training_frame': 'Key_Frame__upload_893634781f588299bbd20d51c98d43a9.hex', 'nfolds': '0', 'keep_cross_validation_models': 'True', 'keep_cross_validation_predictions': 'False', 'keep_cross_validation_fold_assignment': 'False', 'score_each_iteration': 'False', 'fold_assignment': 'auto', 'response_column': 'target', 'ignore_const_cols': 'True', 'stopping_rounds': '0', 'stopping_metric': 'auto', 'stopping_tolerance': '0.001', 'max_runtime_secs': '0.0', 'seed': '-1', 'distribution': 'auto', 'tweedie_power': '1.5', 'categorical_encoding': 'auto', 'quiet_mode': 'True', 'ntrees': '50', 'max_depth': '6', 'min_rows': '1.0', 'min_child_weight': '1.0', 'learn_rate': '0.3', 'eta': '0.3', 'sample_rate': '1.0', 'subsample': '1.0', 'col_sample_rate': '1.0', 'colsample_bylevel': '1.0', 'col_sample_rate_per_tree': '1.0', 'colsample_bytree': '1.0', 'colsample_bynode': '1.0', 'max_abs_leafnode_pred': '0.0', 'max_delta_step': '0.0', 'score_tree_interval': '0', 'min_split_improvement': '0.0', 'gamma': '0.0', 'nthread': '-1', 'build_tree_one_node': 'False', 'calibrate_model': 'False', 'max_bins': '256', 'max_leaves': '0', 'sample_type': 'uniform', 'normalize_type': 'tree', 'rate_drop': '0.0', 'one_drop': 'False', 'skip_drop': '0.0', 'tree_method': 'auto', 'grow_policy': 'depthwise', 'booster': 'gbtree', 'reg_lambda': '1.0', 'reg_alpha': '0.0', 'dmatrix_type': 'auto', 'backend': 'auto', 'gainslift_bins': '-1', 'auc_type': 'auto', 'scale_pos_weight': '1.0'}
有关我的发行版的更多信息:
- OS:蒙特雷 12.3
- 处理器:Apple M1
- Python: 3.9.10
- H2O: 3.36.0.3
我怀疑 Apple M1 是错误的原因,但事实真的如此吗?
抱歉,Apple M1 处理器尚不支持 XGBoost。