Python Can'；t导入scikit学习：导入错误：DLL加载失败：找不到指定的过程

我有python 3.7.6，我正在尝试导入以下软件包：

import pandas as pd
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier

但我得到了以下错误：

---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-1-1ab955ba4021> in <module>
      1 import pandas as pd
----> 2 from sklearn.metrics import accuracy_score
      3 from sklearn.model_selection import train_test_split
      4 from sklearn.tree import DecisionTreeClassifier

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\__init__.py in <module>
     80     from . import _distributor_init  # noqa: F401
     81     from . import __check_build  # noqa: F401
---> 82     from .base import clone
     83     from .utils._show_versions import show_versions
     84 

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\base.py in <module>
     18 
     19 from . import __version__
---> 20 from .utils import _IS_32BIT
     21 
     22 _DEFAULT_TAGS = {

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\__init__.py in <module>
     25 from ..exceptions import DataConversionWarning
     26 from .deprecation import deprecated
---> 27 from .fixes import np_version
     28 from .validation import (as_float_array,
     29                          assert_all_finite,

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\fixes.py in <module>
     16 import scipy.sparse as sp
     17 import scipy
---> 18 import scipy.stats
     19 from scipy.sparse.linalg import lsqr as sparse_lsqr  # noqa
     20 

C:\ProgramData\Anaconda3\lib\site-packages\scipy\stats\__init__.py in <module>
    382 from __future__ import division, print_function, absolute_import
    383 
--> 384 from .stats import *
    385 from .distributions import *
    386 from .morestats import *

C:\ProgramData\Anaconda3\lib\site-packages\scipy\stats\stats.py in <module>
    183 import scipy.special as special
    184 from scipy import linalg
--> 185 from . import distributions
    186 from . import mstats_basic
    187 from ._stats_mstats_common import (_find_repeats, linregress, theilslopes,

C:\ProgramData\Anaconda3\lib\site-packages\scipy\stats\distributions.py in <module>
      8 from __future__ import division, print_function, absolute_import
      9 
---> 10 from ._distn_infrastructure import (entropy, rv_discrete, rv_continuous,
     11                                     rv_frozen)
     12 

C:\ProgramData\Anaconda3\lib\site-packages\scipy\stats\_distn_infrastructure.py in <module>
     23 
     24 # for root finding for discrete distribution ppf, and max likelihood estimation
---> 25 from scipy import optimize
     26 
     27 # for functions of continuous distributions (e.g. moments, entropy, cdf)

C:\ProgramData\Anaconda3\lib\site-packages\scipy\optimize\__init__.py in <module>
    388 
    389 from .optimize import *
--> 390 from ._minimize import *
    391 from ._root import *
    392 from ._root_scalar import *

C:\ProgramData\Anaconda3\lib\site-packages\scipy\optimize\_minimize.py in <module>
     28 from ._trustregion_krylov import _minimize_trust_krylov
     29 from ._trustregion_exact import _minimize_trustregion_exact
---> 30 from ._trustregion_constr import _minimize_trustregion_constr
     31 
     32 # constrained minimization

C:\ProgramData\Anaconda3\lib\site-packages\scipy\optimize\_trustregion_constr\__init__.py in <module>
      2 
      3 
----> 4 from .minimize_trustregion_constr import _minimize_trustregion_constr
      5 
      6 __all__ = ['_minimize_trustregion_constr']

C:\ProgramData\Anaconda3\lib\site-packages\scipy\optimize\_trustregion_constr\minimize_trustregion_constr.py in <module>
      2 import time
      3 import numpy as np
----> 4 from scipy.sparse.linalg import LinearOperator
      5 from .._differentiable_functions import VectorFunction
      6 from .._constraints import (

C:\ProgramData\Anaconda3\lib\site-packages\scipy\sparse\linalg\__init__.py in <module>
    114 from .dsolve import *
    115 from .interface import *
--> 116 from .eigen import *
    117 from .matfuncs import *
    118 from ._onenormest import *

C:\ProgramData\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\__init__.py in <module>
      9 from __future__ import division, print_function, absolute_import
     10 
---> 11 from .arpack import *
     12 from .lobpcg import *
     13 

C:\ProgramData\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\__init__.py in <module>
     20 from __future__ import division, print_function, absolute_import
     21 
---> 22 from .arpack import *

C:\ProgramData\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py in <module>
     43 __all__ = ['eigs', 'eigsh', 'svds', 'ArpackError', 'ArpackNoConvergence']
     44 
---> 45 from . import _arpack
     46 import numpy as np
     47 import warnings

ImportError: DLL load failed: The specified procedure could not be found.

---------------------------------------------------------------------------
ImportError回溯（最近一次呼叫最后一次）
在里面
1进口熊猫作为pd
---->2从sklearn.metrics导入准确性\u分数
3从sklearn.model\u选择导入列车\u测试\u分割
4来自sklearn.tree导入决策树分类程序
C:\ProgramData\Anaconda3\lib\site packages\sklearn\\uuuuu init\uuuuuuuu.py in
80美元。进口(分销商)初始#noqa:F401
81来自。导入(检查)构建(noqa:F401
--->82从基本导入克隆
83从.utils.\u显示\u版本导入显示\u版本
84
中的C:\ProgramData\Anaconda3\lib\site packages\sklearn\base.py
18
19从。导入版本__
--->20 from.utils导入为32位
21
22 \u默认\u标记={
C:\ProgramData\Anaconda3\lib\site packages\sklearn\utils\\uuuuu init\uuuuuuuu.py in
25从..异常导入数据转换警告
26.不推荐导入不推荐导入
--->27 from.fixes导入np_版本
28来自验证导入（作为浮点数组，
29 assert_all_Limited，
中的C:\ProgramData\Anaconda3\lib\site packages\sklearn\utils\fixes.py
16导入scipy.sparse作为sp
17进口西皮
--->18导入scipy.stats
19从scipy.sparse.linalg导入lsqr作为稀疏lsqr#noqa
20
C:\ProgramData\Anaconda3\lib\site packages\scipy\stats\\uuuu init\uuuuu.py in
382来自未来导入部门，打印功能，绝对导入
383
-->384 from.stats导入*
385.从分发导入*
386 from.morests导入*
中的C:\ProgramData\Anaconda3\lib\site packages\scipy\stats\stats.py
183进口scipy.special作为专用
184来自scipy import linalg
-->185.进口分配
186从导入mstats_basic
187 from.\u stats\u mstats\u common import（\u find\u repeats，linregresse，slopes，
中的C:\ProgramData\Anaconda3\lib\site packages\scipy\stats\distributions.py
8来自未来导入部门，打印功能，绝对导入
9
--->10从基础设施导入（熵、离散、连续），
11 rv_（冷冻）
12
C:\ProgramData\Anaconda3\lib\site packages\scipy\stats\\u distn\u infrastructure.py in
23
24#用于离散分布ppf的寻根和最大似然估计
--->25来自scipy导入优化
26
27#对于连续分布函数（例如矩、熵、cdf）
C:\ProgramData\Anaconda3\lib\site packages\scipy\optimize\\uuuuu init\uuuuuuuu.py in
388
389从。优化导入*
-->390发件人。\u最小化导入*
391从.\u根导入*
392从.\u根\u标量导入*
中的C:\ProgramData\Anaconda3\lib\site packages\scipy\optimize\\u minimize.py
28从.\u信任区\u krylov导入\u最小化\u信任\u krylov
29从.\u信任区\u精确导入\u最小化\u信任区\u精确
--->30从.\u托管区\u施工进口\u最小化\u托管区\u施工
31
32#约束极小化
C:\ProgramData\Anaconda3\lib\site packages\scipy\optimize\\u trustregion\u constr\\uuuu init\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
2.
3.
---->4.从最小化信任区域导入最小化信任区域导入
5.
6“全部”=[“最小化信任区域”]
C:\ProgramData\Anaconda3\lib\site packages\scipy\optimize\\u trustregion\u constr\minimize\u trustregion\u constr.py in
2导入时间
3作为np输入numpy
---->4从scipy.sparse.linalg导入线性构造器
5从..可微函数导入向量函数
6从..\u导入约束(
C:\ProgramData\Anaconda3\lib\site packages\scipy\sparse\linalg\\uuuuuu init\uuuuuuuuu.py in
114从dsolve导入*
115.接口导入*
-->116.本征输入*
117.从matfuncs导入*
118自。_ONERMOSTIMPORT*
C:\ProgramData\Anaconda3\lib\site packages\scipy\sparse\linalg\eigen\\uuuuu init\uuuuu.py in
9来自未来导入部门，打印功能，绝对导入
10
--->11.从arpack导入*
12.lobpcg导入*
13
C:\ProgramData\Anaconda3\lib\site packages\scipy\sparse\linalg\eigen\arpack\ \uuuuu init\uuuuuuuuuuu.py in
20来自未来导入部门，打印功能，绝对导入
21
--->22.从arpack导入*
C:\ProgramData\Anaconda3\lib\site packages\scipy\sparse\linalg\eigen\arpack\arpack.py in
43 uuu all uuu=['EIG'、'eigsh'、'svds'、'ArpackError'、'ARPACKNOCONVERCENCE']
44
--->45.进口_arpack
46作为np的进口numpy
47进口警告
ImportError:DLL加载失败：找不到指定的过程。

---

我试过类似帖子中的一些建议（更新anaconda、卸载anaconda、卸载并重新安装pandas NumPy scikit learn等）什么都不管用。我是python新手，希望您能简单解释一下如何解决此问题。

您的scikit学习库似乎没有正确安装。请提供您环境中已安装的库以获取更多信息，现在您可以尝试下面的方法来解决您的问题

conda install --revision=0
conda install python
conda install -c anaconda scikit-learn