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It may be good to provide pure Python implementation of Gradient Descent (instead of SciPy one) for Logistic Regression just for the learning purposes.
The text was updated successfully, but these errors were encountered:
D:\Projetos\Teste Fabio\homemade-machine-learning-master\homemade\logistic_regression_init_.py in
1 """Logistic Regression Module"""
2
----> 3 from .logistic_regression import LogisticRegression
D:\Projetos\Teste Fabio\homemade-machine-learning-master\homemade\logistic_regression\logistic_regression.py in
2
3 import numpy as np
----> 4 from scipy.optimize import minimize
5 from ..utils.features import prepare_for_training
6 from ..utils.hypothesis import sigmoid
D:\aplicativos\Anaconda3\lib\site-packages\scipy\optimize_init_.py in
385
386 from .optimize import *
--> 387 from ._minimize import *
388 from ._root import *
389 from ._root_scalar import *
D:\aplicativos\Anaconda3\lib\site-packages\scipy\optimize_minimize.py in
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
D:\aplicativos\Anaconda3\lib\site-packages\scipy\optimize_trustregion_constr_init_.py in
2
3
----> 4 from .minimize_trustregion_constr import _minimize_trustregion_constr
5
6 all = ['_minimize_trustregion_constr']
D:\aplicativos\Anaconda3\lib\site-packages\scipy\optimize_trustregion_constr\minimize_trustregion_constr.py in
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 (
D:\aplicativos\Anaconda3\lib\site-packages\scipy\sparse_init_.py in
228 import warnings as _warnings
229
--> 230 from .base import *
231 from .csr import *
232 from .csc import *
D:\aplicativos\Anaconda3\lib\site-packages\scipy\sparse\base.py in
7
8 from scipy._lib.six import xrange
----> 9 from scipy._lib._numpy_compat import broadcast_to
10 from .sputils import (isdense, isscalarlike, isintlike,
11 get_sum_dtype, validateaxis, check_reshape_kwargs,
ModuleNotFoundError: No module named 'scipy._lib._numpy_compat'
It may be good to provide pure Python implementation of Gradient Descent (instead of SciPy one) for Logistic Regression just for the learning purposes.
The text was updated successfully, but these errors were encountered: