def test_oracle_maxutil_classifier_is_stable(self):
env = lending.DelayedImpactEnv()
agent_params = classifier_agents.ScoringAgentParams(
feature_keys=['applicant_features'],
group_key='group',
default_action_fn=(lambda: 1),
burnin=1,
threshold_policy=threshold_policies.ThresholdPolicy.SINGLE_THRESHOLD,
convert_one_hot_to_integer=True,
cost_matrix=params.CostMatrix(
fn=0, fp=-1, tp=env.initial_params.interest_rate, tn=0))
agent = oracle_lending_agent.OracleThresholdAgent(
action_space=env.action_space,
observation_space=env.observation_space,
reward_fn=rewards.BinarizedScalarDeltaReward('bank_cash'),
params=agent_params,
env=env)
test_util.run_test_simulation(env=env, agent=agent)
# Drop 0 threshold associated with burn-in.
first_nonzero_threshold = None
for thresh in agent.global_threshold_history:
if thresh > 0:
if first_nonzero_threshold is None:
first_nonzero_threshold = thresh
self.assertAlmostEqual(first_nonzero_threshold, thresh)
# Make sure there is at least one non-zero threshold.
self.assertIsNotNone(first_nonzero_threshold)
def scenario_builder(self):
"""Returns an agent and environment pair."""
env_params = lending_params.DelayedImpactParams(
applicant_distribution=lending_params.two_group_credit_clusters(
cluster_probabilities=self.cluster_probabilities,
group_likelihoods=[self.group_0_prob, 1 - self.group_0_prob]),
bank_starting_cash=self.bank_starting_cash,
interest_rate=self.interest_rate,
cluster_shift_increment=self.cluster_shift_increment,
)
env = lending.DelayedImpactEnv(env_params)
agent_params = classifier_agents.ScoringAgentParams(
feature_keys=['applicant_features'],
group_key='group',
default_action_fn=(lambda: 1),
burnin=self.burnin,
convert_one_hot_to_integer=True,
threshold_policy=self.threshold_policy,
skip_retraining_fn=lambda action, observation: action == 0,
cost_matrix=params.CostMatrix(
fn=0, fp=-1, tp=env_params.interest_rate, tn=0))
agent = oracle_lending_agent.OracleThresholdAgent(
action_space=env.action_space,
reward_fn=rewards.BinarizedScalarDeltaReward(
'bank_cash', baseline=env.initial_params.bank_starting_cash),
observation_space=env.observation_space,
params=agent_params,
env=env)
agent.seed(100)
return env, agent
def test_oracle_lending_agent_interacts(self):
env = lending.DelayedImpactEnv()
agent_params = classifier_agents.ScoringAgentParams(
feature_keys=['applicant_features'],
group_key='group',
default_action_fn=(lambda: 1),
burnin=1,
convert_one_hot_to_integer=True,
cost_matrix=params.CostMatrix(
fn=0, fp=-1, tp=env.initial_params.interest_rate, tn=0))
agent = oracle_lending_agent.OracleThresholdAgent(
action_space=env.action_space,
observation_space=env.observation_space,
reward_fn=rewards.BinarizedScalarDeltaReward('bank_cash'),
params=agent_params,
env=env)
test_util.run_test_simulation(env=env, agent=agent)