This SVC instance is not fitted yet. Call 'fit' with appropriate arguments before using this method

Question

I have used SVC of sklearn to fit the training set, and tried to predict the y_pred by classifier.predict(X_test), but it returned NotFittedError: This SVC instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

I tried restarting the python, it didn't work. I also tried LogisticRegression from sklearn.linear_model and it worked just fine.

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

dataset = pd.read_csv('Social_Network_Ads.csv')
X = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4].values

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)

from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)

from sklearn.svm import SVC
classifier = SVC(kernel = 'linear', random_state = 0)
classifier.fit = (X_train, y_train)

y_pred = classifier.predict(X_test)

I expect the y_pred to contain the predicted values of X_test.

Instead, I got the below error message, NotFittedError: This SVC instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

Answer 1

In the 2nd last line it is :

classifier.fit(X_train, y_train) 

and not

classifier.fit = (X_train, y_train)