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| import numpy as np | |
| import pickle | |
| # loading the saved model | |
| loaded_model = pickle.load(open('trained_model.sav', 'rb')) | |
| input_data = (5,166,72,19,175,25.8,0.587,51) | |
| # changing the input_data to numpy array | |
| input_data_as_numpy_array = np.asarray(input_data) | |
| # reshape the array as we are predicting for one instance | |
| input_data_reshaped = input_data_as_numpy_array.reshape(1,-1) | |
| prediction = loaded_model.predict(input_data_reshaped) | |
| print(prediction) | |
| if (prediction[0] == 0): | |
| print('The person is not diabetic') | |
| else: | |
| print('The person is diabetic') |