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  1. from sklearn import neighbors, linear_model
  2. import numpy as np
  3.  
  4. def train_new_data():
  5.  
  6.     #sgd_clf = linear_model.SGDClassifier()
  7.  
  8.     sgd_clf = linear_model.SGDClassifier()
  9.  
  10.     x1 = [[8, 9], [20, 22]]  
  11.     y1 = [5, 6]  
  12.  
  13.     classes = np.unique(y1)
  14.  
  15.     #print(classes)
  16.  
  17.     sgd_clf.partial_fit(x1,y1,classes=classes)
  18.  
  19.     x2 = [10, 12]
  20.     y2 = 8
  21.  
  22.     x1.append(x2)
  23.     y1.append(y2)
  24.  
  25.     classes = np.unique(y1)
  26.  
  27.     sgd_clf.partial_fit([x2], [y2],classes=classes)
  28.  
  29.     return sgd_clf
  30.  
  31.  
  32.  
  33. if __name__ == "__main__":
  34.  
  35.     print(train_new_data().predict([[20,22]]))
  36.  
Runtime error #stdin #stdout #stderr 0.02s 9268KB
comments (?)
stdin 
Standard input is empty
stdout 
Standard output is empty
stderr 
Traceback (most recent call last):
  File "./prog.py", line 30, in <module>
  File "./prog.py", line 5, in train_new_data
NameError: name 'linear_model' is not defined
https://ideone.com/qtGpnY
language:
Python 3 (python  3.12)
created:
8 years ago
visibility:
public

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