from sklearn import neighbors, linear_model
import numpy as np
 
def train_new_data():
 
    #sgd_clf = linear_model.SGDClassifier()
 
    sgd_clf = linear_model.SGDClassifier(earning_rate = 'constant', eta0 = 0.1, shuffle = False, n_iter = 1,warm_start=True)
 
    x1 = [[8, 9], [20, 22]]  
    y1 = [5, 6]  
 
    classes = np.unique(y1)
 
    #print(classes)
 
    sgd_clf.partial_fit(x1,y1,classes=classes)
 
    x2 = [10, 12]
    y2 = 8
 
    x1.append(x2)
    y1.append(y2)
 
    classes = np.unique(y1)
 
    sgd_clf.partial_fit([x2], [y2],classes=classes)
 
    return sgd_clf
 
 
 
if __name__ == "__main__":
 
    print(train_new_data().predict([[20,22]]))

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