我正在用一些卫星数据做一个简单的PCA分析。所有的陆地点都被移除，平均值和标准差接近于0和1。但是我得到
from sklearn import preprocessing
scaler = preprocessing.StandardScaler()
scaler_sst = scaler.fit(sss_data)
import joblib
joblib.dump(scaler_sst, './scaler_sst.pkl', compress=9)
scaler_sst = joblib.load('./scaler_sst.pkl')
X = scaler_sst.transform(sss_data)
print(X.mean())
print(X.std())
#X.shape
5.7725416769826885e-15
0.9999999999999993
from sklearn.decomposition import pca
skpca=pca.PCA()
skpca.fit(X)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj, include, exclude)
968
969 if method is not None:
--> 970 return method(include=include, exclude=exclude)
971 return None
972 else:
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/sklearn/base.py in _repr_mimebundle_(self, **kwargs)
461 def _repr_mimebundle_(self, **kwargs):
462 """Mime bundle used by jupyter kernels to display estimator"""
--> 463 output = {"text/plain": repr(self)}
464 if get_config()["display"] == 'diagram':
465 output["text/html"] = estimator_html_repr(self)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/sklearn/base.py in __repr__(self, N_CHAR_MAX)
273
274 # use ellipsis for sequences with a lot of elements
--> 275 pp = _EstimatorPrettyPrinter(
276 compact=True, indent=1, indent_at_name=True,
277 n_max_elements_to_show=N_MAX_ELEMENTS_TO_SHOW)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/sklearn/utils/_pprint.py in __init__(self, indent, width, depth, stream, compact, indent_at_name, n_max_elements_to_show)
162 if self._indent_at_name:
163 self._indent_per_level = 1 # ignore indent param
--> 164 self._changed_only = get_config()['print_changed_only']
165 # Max number of elements in a list, dict, tuple until we start using
166 # ellipsis. This also affects the number of arguments of an estimators
KeyError: 'print_changed_only'
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_pprinters=self.type_printers,
701 deferred_pprinters=self.deferred_printers)
--> 702 printer.pretty(obj)
703 printer.flush()
704 return stream.getvalue()
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/IPython/lib/pretty.py in pretty(self, obj)
392 if cls is not object
393 and callable(cls.__dict__.get('__repr__')):
--> 394 return _repr_pprint(obj, self, cycle)
395
396 return _default_pprint(obj, self, cycle)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/IPython/lib/pretty.py in _repr_pprint(obj, p, cycle)
698 """A pprint that just redirects to the normal repr function."""
699 # Find newlines and replace them with p.break_()
--> 700 output = repr(obj)
701 lines = output.splitlines()
702 with p.group():
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/sklearn/base.py in __repr__(self, N_CHAR_MAX)
273
274 # use ellipsis for sequences with a lot of elements
--> 275 pp = _EstimatorPrettyPrinter(
276 compact=True, indent=1, indent_at_name=True,
277 n_max_elements_to_show=N_MAX_ELEMENTS_TO_SHOW)
~/miniconda3/envs/py3_std_maps/lib/python3.8/site-packages/sklearn/utils/_pprint.py in __init__(self, indent, width, depth, stream, compact, indent_at_name, n_max_elements_to_show)
162 if self._indent_at_name:
163 self._indent_per_level = 1 # ignore indent param
--> 164 self._changed_only = get_config()['print_changed_only']
165 # Max number of elements in a list, dict, tuple until we start using
166 # ellipsis. This also affects the number of arguments of an estimators
KeyError: 'print_changed_only'
错误发生在skpca.fit(X)部分。我重新安装了sklearn包和scikit包。我以前用过sklearn的PCA分析，但从来没有发生过这种情况。
我不知道答案，但也许这是一个bug在sklearn:试一试:
import sklearn
sklearn.get_config()
在我的例子中它返回一个字典:
{'assume_finite': False, 'working_memory': 1024, 'print_changed_only': False}
错误提示您的print_changend_only不存在。我的sklearn版本是python 3.6上的"0.21.2"。也许降级sklearn版本会有帮助?