Update README.md

README.md

@@ -123,7 +123,7 @@ X_train = np.random.randn(100, 10)  # 100 samples, 10 features
 Y_train = np.zeros(X_train.shape[0]) # All normal
 X_test = np.random.randn(50, 10)    # Test data
 
-# Fit on training data (for unsupervised setting, no labels needed)
+# Fit on training data (for one-class setting, all labels should be zero)
 model.fit(X_train, Y_train)
 
 # Get anomaly scores