from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

# Load the iris dataset
iris = load_iris()

# Split data into training and validation sets
X_train, X_val, y_train, y_val = train_test_split(,, test_size=0.2, random_state=42)

# Create a KNeighborsClassifier model
model = KNeighborsClassifier()

# Fit the model to the training data, y_train)

# Use the model to predict on the validation data
y_pred = model.predict(X_val)

# Calculate the accuracy score on the validation data
accuracy = accuracy_score(y_val, y_pred)

print("Validation accuracy:", accuracy)