import numpy as np
from sklearn.metrics import mean_squared_error

def model_result(model, X_train, X_test, y_train, y_test):
    model.fit(X_train, y_train)
    y_pred = model.predict(X_test)
    rmse = np.sqrt(mean_squared_error(y_test, y_pred))
    
    return rmse