number of raw dataset: 220
NaNs in GOS----------------- are replaced by 1.0
NaNs in brain--------------- are replaced by 1.0
NaNs in Synek--------------- are replaced by 2.0
NaNs in N20----------------- are replaced by 2.0
NaNs in III----------------- are replaced by 0.0
NaNs in V------------------- are replaced by 0.0
NaNs in III-V/I-III--------- are replaced by 2.0
NaNs in FOUR---------------- are replaced by 0.0
NaNs in GCS----------------- are replaced by 3.0
NaNs in lesion-------------- are replaced by 0.0
number of dataset after filtering: 220 , 0 are removed.
GOS brain Synek N20 III V III-V/I-III FOUR GCS lesion
0 1.0 1.0 2.0 0.0 1.0 1.0 1.0 6.0 3.0 0.0
1 0.0 0.0 0.0 1.0 1.0 1.0 1.0 13.0 8.0 1.0
2 1.0 1.0 2.0 1.0 0.0 0.0 1.0 13.0 8.0 0.0
3 1.0 1.0 2.0 2.0 0.0 2.0 0.0 9.0 5.0 0.0
4 0.0 1.0 2.0 0.0 2.0 2.0 2.0 5.0 6.0 1.0
.. ... ... ... ... ... ... ... ... ... ...
215 1.0 1.0 2.0 0.0 2.0 2.0 0.0 6.0 5.0 0.0
216 1.0 1.0 2.0 2.0 0.0 0.0 0.0 1.0 3.0 0.0
217 1.0 1.0 2.0 2.0 1.0 1.0 2.0 4.0 4.0 0.0
218 1.0 1.0 2.0 2.0 2.0 2.0 2.0 8.0 6.0 0.0
219 1.0 1.0 2.0 0.0 1.0 1.0 1.0 11.0 7.0 1.0
[220 rows x 10 columns]
Sample non-duplication probability = 0.36704176442123
Expected test set number: 80
number of test data: 84
----test set (filtered set - train set)
GOS brain Synek N20 III V III-V/I-III FOUR GCS lesion
1 0.0 0.0 0.0 1.0 1.0 1.0 1.0 13.0 8.0 1.0
2 1.0 1.0 2.0 1.0 0.0 0.0 1.0 13.0 8.0 0.0
3 1.0 1.0 2.0 2.0 0.0 2.0 0.0 9.0 5.0 0.0
11 1.0 1.0 2.0 2.0 0.0 0.0 1.0 0.0 3.0 0.0
12 1.0 1.0 2.0 2.0 2.0 2.0 2.0 0.0 3.0 0.0
.. ... ... ... ... ... ... ... ... ... ...
204 0.0 1.0 2.0 0.0 0.0 0.0 0.0 7.0 7.0 0.0
208 1.0 1.0 2.0 0.0 0.0 0.0 2.0 8.0 7.0 0.0
210 1.0 1.0 2.0 0.0 0.0 0.0 0.0 6.0 5.0 0.0
214 1.0 1.0 2.0 2.0 0.0 0.0 2.0 2.0 6.0 0.0
216 1.0 1.0 2.0 2.0 0.0 0.0 0.0 1.0 3.0 0.0
[84 rows x 10 columns]
number of train data: 136
----train set --------------------
GOS brain Synek N20 III V III-V/I-III FOUR GCS lesion
0 1.0 1.0 2.0 0.0 1.0 1.0 1.0 6.0 3.0 0.0
4 0.0 1.0 2.0 0.0 2.0 2.0 2.0 5.0 6.0 1.0
5 1.0 1.0 2.0 2.0 2.0 2.0 2.0 3.0 5.0 0.0
6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.0 7.0 1.0
7 0.0 0.0 0.0 1.0 0.0 0.0 2.0 2.0 4.0 2.0
.. ... ... ... ... ... ... ... ... ... ...
213 0.0 1.0 0.0 1.0 2.0 2.0 1.0 4.0 3.0 1.0
215 1.0 1.0 2.0 0.0 2.0 2.0 0.0 6.0 5.0 0.0
217 1.0 1.0 2.0 2.0 1.0 1.0 2.0 4.0 4.0 0.0
218 1.0 1.0 2.0 2.0 2.0 2.0 2.0 8.0 6.0 0.0
219 1.0 1.0 2.0 0.0 1.0 1.0 1.0 11.0 7.0 1.0
[136 rows x 10 columns]
trained coeffieciency = [[-0.26056692 1.96192293 1.25820567 0.14211669 -0.1399863 -0.22108856
-0.07519317 -0.43344593]]
number of test data: 84 , 0 are removed.
Accuracy: 0.8333333333333334
Precision: 0.9354838709677419
Recall: 0.8529411764705882

厉害的(ｰ̀εｰ́)