AttributeError: 'numpy.ndarray' object has no attribute 'predict'

Question

I have trained and saved a model :

import numpy as np # load the dataset dataset = np.loadtxt("modiftrain.csv", delimiter=";") # split into input (X) and output (Y) variables X_train = dataset[:,0:5] Y_train = dataset[:,5] from sklearn.naive_bayes import GaussianNB # create Gaussian Naive Bayes model object and train it with the data nb_model = GaussianNB() nb_model.fit(X_train, Y_train.ravel()) # predict values using the training data nb_predict_train = nb_model.predict(X_train) # import the performance metrics library from sklearn import metrics # Accuracy print("Accuracy: {0:.4f}".format(metrics.accuracy_score(Y_train, nb_predict_train))) print() # import the lib to load / Save the model from sklearn.externals import joblib # Save the model joblib.dump(nb_predict_train, "trained-model.pkl") 

Then, i'm loading the model and try to make predictions on a new dataset :

# import the lib to load / Save the model from sklearn.externals import joblib import numpy as np # Load the model nb_predict_train = joblib.load("trained-model.pkl") # load the test dataset df_predict = np.loadtxt("modiftest.csv", delimiter=";") X_train = df_predict nb_predict_train.predict(X_train) print(X_train) 

Here comes the error :

 File "predict01.py", line 14, in <module> nb_predict_train.predict(X_train) AttributeError: 'numpy.ndarray' object has no attribute 'predict' 

Answer 1

You don't want to pickle the predictions but rather the fit.

Change joblib.dump(nb_predict_train, "trained-model.pkl") to joblib.dump(nb_model, "trained-model.pkl")