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I am trying to find the optimal smoothing parameter for additive smoothing with 10-fold cross validation. I wrote the following code:

alphas = list(np.arange(0.0001, 1.5000, 0.0001)) #empty list that stores cv scores cv_scores = [] #perform k fold cross validation for alpha in alphas: naive_bayes = MultinomialNB(alpha=alpha) scores = cross_val_score(naive_bayes, x_train_counts, y_train, cv=10, scoring='accuracy') cv_scores.append(scores.mean()) #changing to misclassification error MSE = [1 - x for x in cv_scores] #determining best alpha optimal_alpha = alphas[MSE.index(min(MSE))] 

I am getting the following error:

--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-21-9d171ddceb31> in <module>() 18 19 #determining best alpha ---> 20 optimal_alpha = alphas[MSE.index(min(MSE))] 21 print('\nThe optimal value of alpha is %f' % optimal_alpha) 22 TypeError: 'int' object is not callable 

I have run the same code for different values of parameters of arange() and K (cross validation). This is the first time I encountered this error. Why?

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    I don't see why you'd run into this - it appears min is a reference to an integer. Did you set min equal to something elsewhere in your ipython workflow? Commented Oct 8, 2018 at 18:33

1 Answer 1

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Somewhere else in your code you have something that looks like this:

 min = 10 

Then you write this:

optimal_alpha = alphas[MSE.index(min(MSE))] 

So, min() is interpreted as a function call.

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2 Comments

Completely correct, except index is function of the list, so you don't have a namespace collision. It would have to be min.
You guys are absolutely right. I recently added a new piece of code in my notebook in which I added a line 'min=999'. Thanks to both of you.

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