def runClassification(spend, marital, hh_size, income):
# define the model
model = LogisticRegression(max_iter=1000)
# dummy training to initialize weights and biases of the model
model.fit(np.array([[0, 0, 0, 0], [1, 1, 1, 1]]), [0, 1])
# Assigning trained weights and biases to the model
model.coef_ = np.array(
[[0.01418876, -0.34609983, 0.14408751, 0.02292672]]) # weights
model.bias_ = np.array([-0.3975337]) # bias
example_instance = np.array(
[[spend, marital, hh_size,
income]]) # [[TOTAL_SPEND, MARITAL, HH_SIZE, INCOME_RANGE]]
# Test the model
prediction = model.predict(example_instance)
return prediction[0].item()
