我正在尝试为分类 categorical_features=['sex','cp','fbs','retecg','exang','thal']创建一个模型 我在 pandas 数据框中有列，例如
df.columns
Index(['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach',
'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'],
dtype='object')
当我在 ( from pycaret.classification import * )
predict_model(best_model, data=df.drop('age',axis=1).tail())#not working
我收到类似的错误
KeyError：“['age'] 不在索引中”
但是正如您在 df.column 的索引中看到的那样，我们有“年龄”，我不知道为什么除了“目标”列之外的所有列都显示错误，我可以在轴 = 1 中删除该列
predict_model(best_model, data=df.drop('target',axis=1).tail())#working
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/tmp/ipykernel_63/493668063.py in <module>
----> 1 predict_model(best_model, data=df.drop('age',axis=1).tail()) #while creating predict_model
/opt/conda/lib/python3.7/site-packages/pycaret/classification.py in predict_model(estimator, data, probability_threshold, encoded_labels, raw_score, round, verbose)
1952 round=round,
1953 verbose=verbose,
-> 1954 ml_usecase=MLUsecase.CLASSIFICATION,
1955 )
1956
/opt/conda/lib/python3.7/site-packages/pycaret/internal/tabular.py in predict_model(estimator, data, probability_threshold, encoded_labels, raw_score, round, verbose, ml_usecase, display)
8665 # prediction starts here
8666
-> 8667 pred = np.nan_to_num(estimator.predict(X_test_))
8668
8669 try:
/opt/conda/lib/python3.7/site-packages/sklearn/utils/metaestimators.py in <lambda>(*args, **kwargs)
117
118 # lambda, but not partial, allows help() to work with update_wrapper
--> 119 out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
120 # update the docstring of the returned function
121 update_wrapper(out, self.fn)
/opt/conda/lib/python3.7/site-packages/sklearn/pipeline.py in predict(self, X, **predict_params)
405 Xt = X
406 for _, name, transform in self._iter(with_final=False):
--> 407 Xt = transform.transform(Xt)
408 return self.steps[-1][-1].predict(Xt, **predict_params)
409
/opt/conda/lib/python3.7/site-packages/pycaret/internal/preprocess.py in transform(self, dataset, y)
362 # drop any columns that were asked to drop
363 data.drop(columns=self.features_todrop, errors="ignore", inplace=True)
--> 364 data = data[self.final_training_columns]
365
366 # also make sure that all the column names are string
/opt/conda/lib/python3.7/site-packages/pandas/core/frame.py in __getitem__(self, key)
3459 if is_iterator(key):
3460 key = list(key)
-> 3461 indexer = self.loc._get_listlike_indexer(key, axis=1)[1]
3462
3463 # take() does not accept boolean indexers
/opt/conda/lib/python3.7/site-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis)
1312 keyarr, indexer, new_indexer = ax._reindex_non_unique(keyarr)
1313
-> 1314 self._validate_read_indexer(keyarr, indexer, axis)
1315
1316 if needs_i8_conversion(ax.dtype) or isinstance(
/opt/conda/lib/python3.7/site-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis)
1375
1376 not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())
-> 1377 raise KeyError(f"{not_found} not in index")
1378
1379
KeyError: "['age'] not in index"