I get the Used the following error when trying to do the score or mean squared error of a single sample :"Found input variables with inconsistent number of samples" for a decision tree regressor model from sklearn to find the chance of having a heart attack based on 13 other parameters. The model seems to work but the metrics tests always give me this kind of error regardless of how I transform the data. Its because the sample test is 1 row whilst the training data is 303 rows but I don't know how to fit them.
import pandas as pd
from sklearn import tree
from sklearn.metrics import mean_squared_error
heart = pd.read_csv('heart.csv')
test = pd.read_csv('Heart_test.csv')
X = heart.iloc[:,0:13]
Y = heart.iloc[:,13:14]
test = test.iloc[:,0:13]
#print(X.head(), '\n', test.head(),'\n')
model = tree.DecisionTreeRegressor()
model = model.fit(X,Y)
y_prediction = model.predict(test)
print(mean_squared_error(Y,y_prediction)