def test_add_rule_lowest_metric_variance(self):
Rule = SimpleRuleMaker()
Rule.add_rule_lowest_metric_variance(metric="precision@",
parameter="100_abs")
assert Rule.create() == [{
'selection_rules': [{
'name': 'lowest_metric_variance',
'n': 1
}],
'shared_parameters': [{
'metric': 'precision@',
'parameter': '100_abs'
}]
}]
def test_add_rule_lowest_metric_variance(self):
Rule = SimpleRuleMaker()
Rule.add_rule_lowest_metric_variance(metric="precision@",
parameter="100_abs")
assert Rule.create() == [{
"selection_rules": [{
"name": "lowest_metric_variance",
"n": 1
}],
"shared_parameters": [{
"metric": "precision@",
"parameter": "100_abs"
}],
}]
from triage.component.audition.rules_maker import SimpleRuleMaker, RandomGroupRuleMaker, TwoMetricsRuleMaker, create_selection_grid Rule1 = SimpleRuleMaker() Rule1.add_rule_best_current_value(metric='precision@', parameter='50_abs', n=3) Rule1.add_rule_best_average_value(metric='precision@', parameter='50_abs', n=3) Rule1.add_rule_lowest_metric_variance(metric='precision@', parameter='50_abs', n=3) Rule1.add_rule_most_frequent_best_dist( metric='precision@', parameter='50_abs', dist_from_best_case=[0.05], n=3 ) Rule1.add_rule_best_avg_recency_weight( metric='precision@', parameter='50_abs', curr_weight=[1.5, 2.0, 5.0], decay_type=['linear'], n=1 ) Rule1.add_rule_best_avg_var_penalized( metric='precision@', parameter='50_abs', stdev_penalty=0.5, n=1 ) Rule2 = RandomGroupRuleMaker(n=1) Rule3 = TwoMetricsRuleMaker() Rule3.add_rule_best_average_two_metrics( metric1='precision@', parameter1='50_abs',