Getting choosey
Next, let's explore hooking up the classifiers that we developed previously. We'll do it within our test framework, but we won't make it a true test yet. Let's just hook it up and poke at it with a stick to start off.
To do so, we can construct a test that must fail so that we can see the output of the strategically placed print statements within our test and ClassifierChooser
. This test will be more complex, since it will more closely mimic a real-world scenario. Here it is:
def given_real_classifiers_and_random_data_test(): class_a_variable_a = numpy.random.normal(loc=51, scale=5, size=1000) class_a_variable_b = numpy.random.normal(loc=5, scale=1, size=1000) class_a_input = zip(class_a_variable_a, class_a_variable_b) class_a_label = ['class a']*len(class_a_input) class_b_variable_a = numpy.random.normal(loc=60, scale=7, size=1000) class_b_variable_b = numpy.random.normal(loc=8, scale=2, size=1000) class_b_input = zip(class_b_variable_a, class_b_variable_b...