Python 产生一些误差的贝叶斯估计

我想了解BayeSestimator是如何工作的。这是我的代码：

将熊猫作为pd导入
进口水
从h2o.estimators导入h2o贝叶斯估计量
df=pd.DataFrame(
{
“a”：列表（范围（10）），
“b”：列表（范围（10）），
“c”：清单（范围（10））
}
)
数据=df.values
h2o.init（）
列车帧=h2o.h2o帧（数据）
nbm=BayeSestimator（）
y=列车框架柱[-1]
nbm.列车（y=y，列车帧=列车帧）

这是我得到的错误：

h2o.exceptions.H2OResponseError: ModelBuilderErrorV3  (water.exceptions.H2OModelBuilderIllegalArgumentException):
    timestamp = 1568829213744
    error_url = '/3/ModelBuilders/naivebayes'
    msg = 'Illegal argument(s) for NaiveBayes model: NaiveBayes_model_python_1568829211691_1.  Details: ERRR on field: _response: Response must be a categorical column'
    dev_msg = 'Illegal argument(s) for NaiveBayes model: NaiveBayes_model_python_1568829211691_1.  Details: ERRR on field: _response: Response must be a categorical column'
    http_status = 412
    values = {'messages': [{'_log_level': 5, '_field_name': '_keep_cross_validation_models', '_message': 'Only for cross-validation.'}, {'_log_level': 5, '_field_name': '_keep_cross_validation_predictions', '_message': 'Only for cross-validation.'}, {'_log_level': 5, '_field_name': '_keep_cross_validation_fold_assignment', '_message': 'Only for cross-validation.'}, {'_log_level': 5, '_field_name': '_fold_assignment', '_message': 'Only for cross-validation.'}, {'_log_level': 5, '_field_name': '_tweedie_power', '_message': 'Only for Tweedie Distribution.'}, {'_log_level': 5, '_field_name': '_tweedie_power', '_message': 'Tweedie power is only used for Tweedie distribution.'}, {'_log_level': 5, '_field_name': '_quantile_alpha', '_message': 'Quantile (alpha) is only used for Quantile regression.'}, {'_log_level': 5, '_field_name': '_max_after_balance_size', '_message': 'Balance classes is false, hide max_after_balance_size'}, {'_log_level': 5, '_field_name': '_balance_classes', '_message': 'Balance classes is only applicable to classification problems.'}, {'_log_level': 5, '_field_name': '_class_sampling_factors', '_message': 'Class sampling factors is only applicable to classification problems.'}, {'_log_level': 5, '_field_name': '_max_after_balance_size', '_message': 'Max after balance size is only applicable to classification problems.'}, {'_log_level': 5, '_field_name': '_max_confusion_matrix_size', '_message': 'Max confusion matrix size is only applicable to classification problems.'}, {'_log_level': 5, '_field_name': '_max_hit_ratio_k', '_message': 'Max K-value for hit ratio is only applicable to multi-class classification problems.'}, {'_log_level': 5, '_field_name': '_max_confusion_matrix_size', '_message': 'Only for multi-class classification problems.'}, {'_log_level': 5, '_field_name': '_max_after_balance_size', '_message': 'Only used with balanced classes'}, {'_log_level': 5, '_field_name': '_class_sampling_factors', '_message': 'Class sampling factors is only applicable if balancing classes.'}, {'_log_level': 1, '_field_name': '_response', '_message': 'Response must be a categorical column'}, {'_log_level': 5, '_field_name': '_balance_classes', '_message': 'Balance classes is not applicable to NaiveBayes.'}, {'_log_level': 5, '_field_name': '_class_sampling_factors', '_message': 'Class sampling factors is not applicable to NaiveBayes.'}, {'_log_level': 5, '_field_name': '_max_after_balance_size', '_message': 'Max after balance size is not applicable to NaiveBayes.'}], 'algo': 'NaiveBayes', 'parameters': {'_train': {'name': 'Key_Frame__upload_9cb9251216ede45dd909d3e9af81477a.hex', 'type': 'Key'}, '_valid': None, '_nfolds': 0, '_keep_cross_validation_models': True, '_keep_cross_validation_predictions': False, '_keep_cross_validation_fold_assignment': False, '_parallelize_cross_validation': True, '_auto_rebalance': True, '_seed': -1, '_fold_assignment': 'AUTO', '_categorical_encoding': 'AUTO', '_max_categorical_levels': 10, '_distribution': 'AUTO', '_tweedie_power': 1.5, '_quantile_alpha': 0.5, '_huber_alpha': 0.9, '_ignored_columns': None, '_ignore_const_cols': True, '_weights_column': None, '_offset_column': None, '_fold_column': None, '_check_constant_response': True, '_is_cv_model': False, '_score_each_iteration': False, '_max_runtime_secs': 0.0, '_stopping_rounds': 0, '_stopping_metric': 'AUTO', '_stopping_tolerance': 0.001, '_response_column': 'C3', '_balance_classes': False, '_max_after_balance_size': 5.0, '_class_sampling_factors': None, '_max_confusion_matrix_size': 20, '_checkpoint': None, '_pretrained_autoencoder': None, '_custom_metric_func': None, '_custom_distribution_func': None, '_export_checkpoints_dir': None, '_laplace': 0.0, '_eps_sdev': 0.0, '_min_sdev': 0.001, '_eps_prob': 0.0, '_min_prob': 0.001, '_compute_metrics': True}, 'error_count': 2}
    exception_msg = 'Illegal argument(s) for NaiveBayes model: NaiveBayes_model_python_1568829211691_1.  Details: ERRR on field: _response: Response must be a categorical column'
    stacktrace =
.
.
.
parameters = {'__meta': {'schema_version': 3, 'schema_name': 'NaiveBayesParametersV3', 'schema_type': 'NaiveBayesParameters'}, 'model_id': None, 'training_frame': {'__meta': {'schema_version': 3, 'schema_name': 'FrameKeyV3', 'schema_type': 'Key<Frame>'}, 'name': 'Key_Frame__upload_9cb9251216ede45dd909d3e9af81477a.hex', 'type': 'Key<Frame>', 'URL': '/3/Frames/Key_Frame__upload_9cb9251216ede45dd909d3e9af81477a.hex'}, 'validation_frame': None, 'nfolds': 0, 'keep_cross_validation_models': True, 'keep_cross_validation_predictions': False, 'keep_cross_validation_fold_assignment': False, 'parallelize_cross_validation': True, 'distribution': 'AUTO', 'tweedie_power': 1.5, 'quantile_alpha': 0.5, 'huber_alpha': 0.9, 'response_column': {'__meta': {'schema_version': 3, 'schema_name': 'ColSpecifierV3', 'schema_type': 'VecSpecifier'}, 'column_name': 'C3', 'is_member_of_frames': None}, 'weights_column': None, 'offset_column': None, 'fold_column': None, 'fold_assignment': 'AUTO', 'categorical_encoding': 'AUTO', 'max_categorical_levels': 10, 'ignored_columns': None, 'ignore_const_cols': True, 'score_each_iteration': False, 'checkpoint': None, 'stopping_rounds': 0, 'max_runtime_secs': 0.0, 'stopping_metric': 'AUTO', 'stopping_tolerance': 0.001, 'custom_metric_func': None, 'custom_distribution_func': None, 'export_checkpoints_dir': None, 'balance_classes': False, 'class_sampling_factors': None, 'max_after_balance_size': 5.0, 'max_confusion_matrix_size': 20, 'max_hit_ratio_k': 0, 'laplace': 0.0, 'min_sdev': 0.001, 'eps_sdev': 0.0, 'min_prob': 0.001, 'eps_prob': 0.0, 'compute_metrics': True, 'seed': -1}
    messages = [{'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'keep_cross_validation_models', 'message': 'Only for cross-validation.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'keep_cross_validation_predictions', 'message': 'Only for cross-validation.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'keep_cross_validation_fold_assignment', 'message': 'Only for cross-validation.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'fold_assignment', 'message': 'Only for cross-validation.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'tweedie_power', 'message': 'Only for Tweedie Distribution.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'tweedie_power', 'message': 'Tweedie power is only used for Tweedie distribution.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'quantile_alpha', 'message': 'Quantile (alpha) is only used for Quantile regression.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_after_balance_size', 'message': 'Balance classes is false, hide max_after_balance_size'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'balance_classes', 'message': 'Balance classes is only applicable to classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'class_sampling_factors', 'message': 'Class sampling factors is only applicable to classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_after_balance_size', 'message': 'Max after balance size is only applicable to classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_confusion_matrix_size', 'message': 'Max confusion matrix size is only applicable to classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_hit_ratio_k', 'message': 'Max K-value for hit ratio is only applicable to multi-class classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_confusion_matrix_size', 'message': 'Only for multi-class classification problems.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_after_balance_size', 'message': 'Only used with balanced classes'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'class_sampling_factors', 'message': 'Class sampling factors is only applicable if balancing classes.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'ERRR', 'field_name': 'response', 'message': 'Response must be a categorical column'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'balance_classes', 'message': 'Balance classes is not applicable to NaiveBayes.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'class_sampling_factors', 'message': 'Class sampling factors is not applicable to NaiveBayes.'}, {'__meta': {'schema_version': 3, 'schema_name': 'ValidationMessageV3', 'schema_type': 'ValidationMessage'}, 'message_type': 'TRACE', 'field_name': 'max_after_balance_size', 'message': 'Max after balance size is not applicable to NaiveBayes.'}]
    error_count = 2

h2o.exceptions.H2OResponseError:ModelBuilderError3（water.exceptions.H2OModelBuilderAllegalArgumentException）：
时间戳=1568829213744
错误_url='/3/ModelBuilders/naivebayes'
msg='NaiveBayes模型的非法参数：NaiveBayes_model_python_156882; 9211691_1。详细信息：ERRR on field:\u response:response必须是分类列'
dev_msg='NaiveBayes模型的非法参数：NaiveBayes_model_python_156882; 9211691_1。详细信息：ERRR on field:\u response:response必须是分类列'
http_status=412
值={'messages'：[{'u log'u level'：5'，'u field'u name'：'u keep'u cross'u validation'u models'，'u message'：'仅用于交叉验证。}，{'u log'level'：5'，'u field'u name'：'u keep'u cross'u validation'u predictions'，'u message'：'仅用于交叉验证。}，{“日志级别”：5，“字段名称”：“仅用于交叉验证”，“消息级别”：5，“字段名称”：“仅用于交叉验证”，“消息级别”：5，“字段名称”：“仅用于交叉验证”。}，{{{}{}{}{}日志}级别：5，{}}}}}{}字段}}}}}}}}}名称}}}}}}}}}}}}}}}}}}分位数}}}}}}}}，{“日志级别”：5，“字段名称”：“余额大小”后的“最大值”，“消息”：“余额类为假，在余额大小后隐藏最大值”}，{“日志级别”：5，“字段名称”：“余额大小”后的“最大值”，“消息”：“余额类仅适用于分类问题”。}，{“日志级别”：5，“字段名称”：“类采样系数”，“消息”：“类采样系数仅适用于分类问题”。}，{“日志级别”：5，“字段名称”：“平衡大小后的最大值”，“平衡大小后的最大值仅适用于分类问题”。}，{“日志级别”：5，“字段名称”：“最大混淆矩阵大小”，“消息”：“最大混淆矩阵大小仅适用于分类问题”。}，{“日志级别”：5，“字段名称”：“最大命中率k”，“消息：”命中率的最大k值仅适用于多类分类问题。}，{“日志级别”：5，“字段名称”：“最大混乱矩阵大小”，“消息”仅适用于多类分类问题。}，{“日志级别”：5，“字段名称”：“平衡大小后的最大混乱矩阵大小”，“消息”仅用于平衡类”}，{“日志级别”：5，“字段名称”：“类采样系数”，“消息”：“类采样系数仅在平衡类时适用”。}，{“日志级别”：1，“字段名称”：“响应”，“消息”：“响应必须是分类列”}，{“日志级别”：5，“字段名称”：“平衡类”，“消息”：“平衡类不适用于NaiveBayes”。}，{“日志级别”：5，“字段名称”：“采样系数”，“消息”：“类采样系数不适用于NaiveBayes”。}，{“日志”级别：5，“字段名称”：“平衡大小后的最大值”，“消息”：平衡大小后的最大值不适用于NaiveBayes.}]，“算法”：“NaiveBayes”，“参数”：“{”列：{“名称”：“键帧上传”9CB9251216ED45DD909D3E9AF81477A.hex”，“类型”：“键”}，“有效”：无，“\u交叉验证”：0，“\u保持交叉验证\u模型”：真，“\u保持交叉验证\u预测”：假，“\u保持交叉验证\u折叠指定”：假，“\u并行交叉验证”：真，“\u自动再平衡”：真，“\u种子”：-1，“\u折叠指定”：“自动”，“分类编码”：“自动”，“最大分类级别”：10，“\u分布”：“AUTO”和“tweedie-power”：1.5，“分位数”和“alpha”：0.5，“huber-alpha”：0.9，“忽略列”：无，“忽略列”：真，“权重列”：无，“偏移列”：无，“折叠列”：无，“检查常量响应”：真，“是cv模型”：假，“每次迭代得分”：假，“最大运行时”：0.0，“停止”ng_度量“：“自动”、“停止_公差”：0.001、“响应_列”：“C3”、“平衡_类”：False、“平衡_大小后的最大值”：5.0、“采样_系数”：None、“最大值混淆_矩阵_大小”：20、“检查点”：None、“预训练的自动编码器”：None、“自定义_度量_函数”：None、“自定义分布函数”：None、“导出_检查点”：Nonene，“U-laplace”：0.0，“U-eps\U-sdev”：0.0，“U-min\U-sdev”：0.001，“U-eps\U-prob”：0.0，“U-min\U-prob”：0.001，“U-compute\U-metrics”：True}，“error\U-count”：2}
exception_msg='NaiveBayes模型的非法参数：NaiveBayes_model_python_156882; u 9211691_1。详细信息：ERRR on field:_response:response必须是分类列'
堆栈跟踪=
.
.
.
参数={uuuuu meta'：{'schema_version'：3，'schema_name'：'NaiveBayesParametersV3'，'schema_type'：'NaiveBayesParameters'}，'model_id'：None，'training_frame'：{'schema_version'：3，'schema_name'：'FrameKeyV3'，'schema_type'：'Key'}，'name'：'Key\u Frame\u upload\u 9cb9251216ede45dd909d3e9af81477a.hex'，'type'：'Key'，'URL'：'/3/Frames/Key\u Frame\u upload\u 9cb9251216ede45dd909d3e9af81477a.hex'}，“验证框架”：无，'Nfold'：0，'keep_cross_validation_models'：True，'keep_cross_validation_predictions'：False，'keep_cross_validation_fold_assignment'：False，'parallelize_cross_validation'：True，'distribution'：'AUTO'，'tweedie_power'：1.5，'quantile_alpha'：0.5，'huber_alpha'：0.9，'response_column'：{'{'schema_version'：3，'schema_name'：'ColSpecifierV3'，'schema_type'：'vecsspecifier'}，'column_name'：'C3'，'is_member_of_frames'：N
train_frame[y] = train_frame[y].asfactor()