[英]I try imputing in sklearn but I have an error
I try below code but I have some error.我尝试下面的代码,但我有一些错误。
imp=SimpleImputer(missing_values='NaN',strategy="mean")
col = veriler.iloc[:,1:4].values
type(col) ##numpy.ndarray
imp=imp.fit(col)
ValueError: Input contains NaN, infinity or a value too large for dtype('float64'). ValueError:输入包含 NaN、无穷大或对于 dtype('float64') 来说太大的值。
You need to convert the infinity values to a bounded value to apply imputation.您需要将无穷大值转换为有界值以应用插补。 np.nan_to_num clips
nan
, inf
and -inf
to workable values. np.nan_to_num 将
nan
、 inf
和-inf
剪辑为可行的值。
For example:例如:
import numpy as np
from sklearn.impute import SimpleImputer
imp_mean = SimpleImputer(missing_values=np.nan, strategy='mean')
X = [[7, np.inf, 3], [4, np.nan, 6], [10, 5, 9]]
X = np.nan_to_num(X, nan=-9999, posinf=33333333, neginf=-33333333)
imp_mean.fit(X)
>>> SimpleImputer(add_indicator=False, copy=True, fill_value=None,
missing_values=nan, strategy='mean', verbose=0)
For transform also, this can be applied:对于变换,这也可以应用:
X = [[np.nan, 2, 3], [4, np.nan, 6], [10, np.nan, 9], [np.nan, np.inf, -np.inf]]
X = np.nan_to_num(X, nan=-9999, posinf=33333333, neginf=-33333333)
print(imp_mean.transform(X))
>>>
[[-9.9990000e+03 2.0000000e+00 3.0000000e+00]
[ 4.0000000e+00 -9.9990000e+03 6.0000000e+00]
[ 1.0000000e+01 -9.9990000e+03 9.0000000e+00]
[-9.9990000e+03 3.3333333e+07 -3.3333333e+07]]
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