def given_a_sleeping_dog_test():
customer_segment = ('60602', 'male')
classification_model = SimplisticClasses.DumbClassifier({
('control', ) + customer_segment:
0.50,
('variant', ) + customer_segment:
0.45,
})
regression_model = SimplisticClasses.AllCasesHaveSameProfitRegressionModel(
)
ad_name = SimplisticClasses.assign_ad_for(customer_segment,
classification_model,
regression_model)
assert ad_name == 'control', "Should let sleeping dogs lie."
def given_a_variant_that_does_NOT_improve_on_probability_of_ordering_over_control_test(
):
customer_segment = ('60626', 'male')
classification_model = SimplisticClasses.DumbClassifier({
('control', ) + customer_segment:
0.45,
('variant', ) + customer_segment:
0.45,
})
regression_model = SimplisticClasses.AllCasesHaveSameProfitRegressionModel(
)
ad_name = SimplisticClasses.assign_ad_for(customer_segment,
classification_model,
regression_model)
assert ad_name == 'control', "Should choose to NOT advertise"
def given_variant_improves_over_control_just_enough_to_warrant_advertising_cost_test(
):
customer_segment = ('60626', 'female')
classification_model = SimplisticClasses.DumbClassifier({
('control', ) + customer_segment:
0.60,
('variant', ) + customer_segment:
0.65,
})
regression_model = SimplisticClasses.AllCasesHaveSameProfitRegressionModel(
)
ad_name = SimplisticClasses.assign_ad_for(customer_segment,
classification_model,
regression_model,
ad_cost=0.60)
assert ad_name == 'variant', "Should choose to advertise"
def given_any_input_test():
regression_model = SimplisticClasses.AllCasesHaveSameProfitRegressionModel(
)
results = regression_model.predict(input=(42, 'hai'))
assert results == 12.25, "Should be a constant amount regardless of the input."