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result.txt
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Python 3.8.8rc1 (tags/v3.8.8rc1:dfd7d68, Feb 17 2021, 11:01:21) [MSC v.1928 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license()" for more information.
>>>
========= RESTART: C:\Users\Desktop\Feature selection\main.py =========
Id Cl.thickness Cell.size ... Normal.nucleoli Mitoses Class
0 1000025 5 1 ... 1 1 0
1 1002945 5 4 ... 2 1 0
2 1015425 3 1 ... 1 1 0
3 1016277 6 8 ... 7 1 0
4 1017023 4 1 ... 1 1 0
.. ... ... ... ... ... ... ...
694 776715 3 1 ... 1 1 0
695 841769 2 1 ... 1 1 0
696 888820 5 10 ... 10 2 1
697 897471 4 8 ... 6 1 1
698 897471 4 8 ... 4 1 1
[699 rows x 10 columns]
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
Features name:
['Id', 'Cl.thickness', 'Cell.size', 'Cell.shape', 'Marg.adhesion', 'Epith.c.size', 'Bl.cromatin', 'Normal.nucleoli', 'Mitoses', 'Class']
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
*****************Univarint method resuls*****************
[ 4.515 733.207 1408.527 1419.306 657.794 608.72 933.287 717.628
152.04 ]
[[0.5 0.1 0.1 0.3]
[0.5 0.4 0.4 0.3]
[0.3 0.1 0.1 0.3]]
[ 4.515 152.04 608.72 657.794 717.628 733.207 933.287 1408.527
1419.306]
list of best feature in univariant methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
6 Bl.cromatin
7 Normal.nucleoli
univariant running time: 0.031200170516967773 seconds
*****************Model based (single fit) methods resuls*****************
[-0.005 0.117 0.061 0.096 0.058 0.023 0.084 0.05 0. ]
list of best feature in model_based methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
6 Bl.cromatin
model_based running time: 0.07800006866455078 seconds
*****************changing_Lasso_alpha methods resuls*****************
[-0. 0. 0. 0. 0. 0. 0. 0. 0.]
list of best feature in changing_Lasso_alpha methods:
0 Id
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
changing_Lasso_alpha running time: 0.015599966049194336 seconds
*****************recursive_feature_elimination methods resuls*****************
[8 3 4 1 5 7 2 6 9]
list of best feature in Recursive Feature Eliminate methods:
0 Id
4 Marg.adhesion
5 Epith.c.size
7 Normal.nucleoli
8 Mitoses
ref running time: 0.015599727630615234 seconds
*****************sequentialfeatureselector methods resuls*****************
(0, 1, 2, 3, 4, 5, 6, 7, 8)
list of best feature in sequentialfeatureselector methods:
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
sequentialfeatureselector running time: 0.015599966049194336 seconds
None
*****************Original data set prediction*****************
Accuracy: 0.966 (0.022)
*****************Univarint Test prediction*****************
Accuracy: 0.954 (0.024)
*****************Model based (single fit) Test prediction*****************
Accuracy: 0.956 (0.028)
*****************changing_Lasso_alpha methods Test prediction*****************
Accuracy: 0.968 (0.021)
*****************recursive_feature_elimination methods Test prediction*****************
Accuracy: 0.924 (0.029)
*****************sequentialfeatureselector methods Test prediction*****************
Accuracy: 0.935 (0.031)
>>>
========= RESTART: C:\Users\Amadelli\Desktop\Feature selection\main.py =========
Id Cl.thickness Cell.size ... Normal.nucleoli Mitoses Class
0 1000025 5 1 ... 1 1 0
1 1002945 5 4 ... 2 1 0
2 1015425 3 1 ... 1 1 0
3 1016277 6 8 ... 7 1 0
4 1017023 4 1 ... 1 1 0
.. ... ... ... ... ... ... ...
694 776715 3 1 ... 1 1 0
695 841769 2 1 ... 1 1 0
696 888820 5 10 ... 10 2 1
697 897471 4 8 ... 6 1 1
698 897471 4 8 ... 4 1 1
[699 rows x 10 columns]
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
Features name:
['Id', 'Cl.thickness', 'Cell.size', 'Cell.shape', 'Marg.adhesion', 'Epith.c.size', 'Bl.cromatin', 'Normal.nucleoli', 'Mitoses', 'Class']
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
*****************Univarint method resuls*****************
[ 4.515 733.207 1408.527 1419.306 657.794 608.72 933.287 717.628
152.04 ]
[[0.5 0.1 0.1 0.3]
[0.5 0.4 0.4 0.3]
[0.3 0.1 0.1 0.3]]
[ 4.515 152.04 608.72 657.794 717.628 733.207 933.287 1408.527
1419.306]
list of best feature in univariant methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
6 Bl.cromatin
7 Normal.nucleoli
univariant running time: 0.015599966049194336 seconds
*****************Model based (single fit) methods resuls*****************
[-0.005 0.117 0.061 0.096 0.058 0.023 0.084 0.05 0. ]
list of best feature in model_based methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
6 Bl.cromatin
model_based running time: 0.07800030708312988 seconds
*****************changing_Lasso_alpha methods resuls*****************
[-0. 0. 0. 0. 0. 0. 0. 0. 0.]
list of best feature in changing_Lasso_alpha methods:
0 Id
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
changing_Lasso_alpha running time: 0.0 seconds
*****************recursive_feature_elimination methods resuls*****************
[8 3 4 1 5 7 2 6 9]
list of best feature in Recursive Feature Eliminate methods:
0 Id
4 Marg.adhesion
5 Epith.c.size
7 Normal.nucleoli
8 Mitoses
ref running time: 0.015599966049194336 seconds
*****************sequentialfeatureselector methods resuls*****************
(0, 1, 2, 3, 4, 5, 6, 7, 8)
list of best feature in sequentialfeatureselector methods:
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
sequentialfeatureselector running time: 0.015599966049194336 seconds
None
*****************Original data set prediction*****************
Accuracy: 0.965 (0.019)
*****************Univarint Test prediction*****************
Accuracy: 0.958 (0.019)
*****************Model based (single fit) Test prediction*****************
Accuracy: 0.958 (0.023)
*****************changing_Lasso_alpha methods Test prediction*****************
Accuracy: 0.965 (0.019)
*****************recursive_feature_elimination methods Test prediction*****************
Accuracy: 0.927 (0.025)
*****************sequentialfeatureselector methods Test prediction*****************
Accuracy: 0.939 (0.022)
>>>
========= RESTART: C:\Users\Amadelli\Desktop\Feature selection\main.py =========
Id Cl.thickness Cell.size ... Normal.nucleoli Mitoses Class
0 1000025 5 1 ... 1 1 0
1 1002945 5 4 ... 2 1 0
2 1015425 3 1 ... 1 1 0
3 1016277 6 8 ... 7 1 0
4 1017023 4 1 ... 1 1 0
.. ... ... ... ... ... ... ...
694 776715 3 1 ... 1 1 0
695 841769 2 1 ... 1 1 0
696 888820 5 10 ... 10 2 1
697 897471 4 8 ... 6 1 1
698 897471 4 8 ... 4 1 1
[699 rows x 10 columns]
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
Features name:
['Id', 'Cl.thickness', 'Cell.size', 'Cell.shape', 'Marg.adhesion', 'Epith.c.size', 'Bl.cromatin', 'Normal.nucleoli', 'Mitoses', 'Class']
dataset description
Id Cl.thickness ... Mitoses Class
count 6.990000e+02 699.000000 ... 699.000000 699.000000
mean 1.071704e+06 4.417740 ... 1.589413 0.344778
std 6.170957e+05 2.815741 ... 1.715078 0.475636
min 6.163400e+04 1.000000 ... 1.000000 0.000000
25% 8.706885e+05 2.000000 ... 1.000000 0.000000
50% 1.171710e+06 4.000000 ... 1.000000 0.000000
75% 1.238298e+06 6.000000 ... 1.000000 1.000000
max 1.345435e+07 10.000000 ... 10.000000 1.000000
[8 rows x 10 columns]
*****************Univarint method resuls*****************
[ 4.515 733.207 1408.527 1419.306 657.794 608.72 933.287 717.628
152.04 ]
[[0.5 0.1 0.1 0.3]
[0.5 0.4 0.4 0.3]
[0.3 0.1 0.1 0.3]]
[ 4.515 152.04 608.72 657.794 717.628 733.207 933.287 1408.527
1419.306]
list of best feature in univariant methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
6 Bl.cromatin
7 Normal.nucleoli
univariant running time: 0.2130122184753418 seconds
*****************Model based (single fit) methods resuls*****************
[-0.005 0.117 0.061 0.096 0.058 0.023 0.084 0.05 0. ]
list of best feature in model_based methods:
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
6 Bl.cromatin
model_based running time: 0.480027437210083 seconds
*****************changing_Lasso_alpha methods resuls*****************
[-0. 0. 0. 0. 0. 0. 0. 0. 0.]
list of best feature in changing_Lasso_alpha methods:
0 Id
1 Cl.thickness
2 Cell.size
3 Cell.shape
4 Marg.adhesion
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
changing_Lasso_alpha running time: 0.013000726699829102 seconds
*****************recursive_feature_elimination methods resuls*****************
[8 3 4 1 5 7 2 6 9]
list of best feature in Recursive Feature Eliminate methods:
0 Id
4 Marg.adhesion
5 Epith.c.size
7 Normal.nucleoli
8 Mitoses
ref running time: 0.06400370597839355 seconds
*****************sequentialfeatureselector methods resuls*****************
(0, 1, 2, 3, 4, 5, 6, 7, 8)
list of best feature in sequentialfeatureselector methods:
5 Epith.c.size
6 Bl.cromatin
7 Normal.nucleoli
8 Mitoses
sequentialfeatureselector running time: 0.04000234603881836 seconds
None
*****************Original data set prediction*****************
Accuracy: 0.966 (0.017)
*****************Univarint Test prediction*****************
Accuracy: 0.958 (0.018)
*****************Model based (single fit) Test prediction*****************
Accuracy: 0.956 (0.023)
*****************changing_Lasso_alpha methods Test prediction*****************
Accuracy: 0.967 (0.017)
*****************recursive_feature_elimination methods Test prediction*****************
Accuracy: 0.926 (0.030)
*****************sequentialfeatureselector methods Test prediction*****************
Accuracy: 0.935 (0.023)
>>>