TypeError: fit() missing 1 required positional argument: 'y'

Question

I am trying to predict economic cycles using Gaussian Naive Bayes "Classifier".

data (input X) :

             SPY    Interest Rate    Unemployment   Employment  CPI Date                     1997-01-02   56.05     7.82            9.7           3399.9     159.100 1997-02-03   56.58     7.65            9.8           3402.8     159.600 1997-03-03   54.09     7.90            9.9           3414.7     160.000 

target (output Y) :

    Economy 0   Expansion 1   Expansion 2   Expansion 3   Expansion 

Below is my code:

from sklearn.naive_bayes import GaussianNB from sklearn import metrics from sklearn.cross_validation import train_test_split X = data Y = target model = GaussianNB X_train, X_test, Y_train, Y_test = train_test_split(X,Y) model.fit(X_train, Y_train) 

Below is Error:

TypeError                                 Traceback (most recent call last) <ipython-input-132-b0975752a19f> in <module>()   6 model = GaussianNB   7 X_train, X_test, Y_train, Y_test = train_test_split(X,Y)   ----> 8 model.fit(X_train, Y_train)    TypeError: fit() missing 1 required positional argument: 'y' 

What am I doing wrong? How can I resolve this issue /error ?

Answer 1

You forgot the parenthesis "()" in:

model = GaussianNB()