成功解决 ValueError: feature_names mismatch training data did not have the following fields - 代码天地

成功解决 ValueError: feature_names mismatch training data did not have the following fields

其他 2019-03-21 03:07:03 阅读次数: 0

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转载自blog.csdn.net/qq_41185868/article/details/88676054

成功解决 ValueError: feature_names mismatch training data did not have the following fields

成功解决ValueError: Number of passed names did not match number of header fields in the file

在用机器学习去训练模型，预测数据的时候，出现ValueError: feature_names mismatch:

成功解决xgboost\core.py", ValueError: feature_names may not contain [, ] or

成功解决ValueError: feature_names mismatch: [‘f0‘, ‘f1‘, ‘f2‘, ‘f3‘, ‘f4‘] expected f3, f1, f2, f0, f4

机器学习平台系列——XGB feature_names mismatch 问题解决方案

成功解决ValueError: DataFrame.dtypes for data must be int, float or bool.Did not expect the data types

成功解决raise TypeError(‘Unexpected feature_names type‘)TypeError: Unexpected feature_names type

已解决ValueError: Length mismatch: Expected axis has 5 elements, new values have 4 elements

已解决ValueError: Length mismatch: Expected axis has 2 elements, new values have 3 elements

tensorflow2.0 ValueError: Empty training data.报错

完美解决None of the following candidates is applicable because of receiver type mismatch:

ValueError: mode mismatch

成功解决ValueError: Data is not binary and pos_label is not specified

The following packages have unmet dependencies问题解决

成功解决ParserError: Error tokenizing data. C error: Expected 2 fields in line 53, saw 3

【Debug记录】pytorch转onnx报错：[ CUDALongType{1} ]) of traced region did not have observable data dependenc

The following packages have unmet dependencies

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二、gulp报错The following tasks did not complete

lightgbm : wrong size of feature_names

成功解决pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 48, saw 2

成功解决pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 49, saw 2

成功解决pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 4, saw 2

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