I am trying to implement a K-NN algorithm using scikit-learn.
This is how my code looks like:

```
X = df.drop(columns=['Purchased'])
y = df['Purchased'].values
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, 
test_size=0.3,stratify=y)
from sklearn.preprocessing import StandardScaler  
scaler = StandardScaler()  
scaler.fit(X_train)
X_train = scaler.transform(X_train)  
X_test = scaler.transform(X_test)  
from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier(n_neighbors = 3)
knn.fit(X_train,y_train)
knn.predict(X_test)
knn.score(X_test, y_test)
from sklearn.metrics import classification_report, confusion_matrix  
print(confusion_matrix(y_test, knn))  
print(classification_report(y_test, knn)) 

```

After running the 2 last outputs I am getting this message:

```
TypeError: Expected sequence or array-like, got estimator KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',
           metric_params=None, n_jobs=None, n_neighbors=3, p=2,
           weights='uniform')

```

Does anyone know what is the problem?
Thanks!