---------------------------------------------------------------------------
StopIteration Traceback (most recent call last)
File /usr/local/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:179, in BayesianOptimization.maximize(self, init_points, n_iter, acq, kappa, kappa_decay, kappa_decay_delay, xi, **gp_params)
178 try:
--> 179 x_probe = next(self._queue)
180 except StopIteration:
File /usr/local/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:25, in Queue.__next__(self)
24 if self.empty:
---> 25 raise StopIteration("Queue is empty, no more objects to retrieve.")
26 obj = self._queue[0]
StopIteration: Queue is empty, no more objects to retrieve.
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
Input In [22], in <module>
36 optimizer = BayesianOptimization( f=xgboost_hyper_param, pbounds=pbounds, random_state=1)
37 # init_points: 초기 랜덤 포인트 갯수
38 # acq='ei': Expected Improvement
39 # xi=0.01: exploration(불확실성이 가장 높은 점 근처에 최적값이 존재할 것이라는 가정으로 계산된 값) 강도 (보통 0.01)
---> 40 optimizer.maximize(init_points=10, n_iter=100, acq='ei', xi=0.01)
File /usr/local/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:182, in BayesianOptimization.maximize(self, init_points, n_iter, acq, kappa, kappa_decay, kappa_decay_delay, xi, **gp_params)
180 except StopIteration:
181 util.update_params()
--> 182 x_probe = self.suggest(util)
183 iteration += 1
185 self.probe(x_probe, lazy=False)
File /usr/local/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:131, in BayesianOptimization.suggest(self, utility_function)
128 self._gp.fit(self._space.params, self._space.target)
130 # Finding argmax of the acquisition function.
--> 131 suggestion = acq_max(
132 ac=utility_function.utility,
133 gp=self._gp,
134 y_max=self._space.target.max(),
135 bounds=self._space.bounds,
136 random_state=self._random_state
137 )
139 return self._space.array_to_params(suggestion)
File /usr/local/lib/python3.9/site-packages/bayes_opt/util.py:65, in acq_max(ac, gp, y_max, bounds, random_state, n_warmup, n_iter)
62 continue
64 # Store it if better than previous minimum(maximum).
---> 65 if max_acq is None or -res.fun[0] >= max_acq:
66 x_max = res.x
67 max_acq = -res.fun[0]
TypeError: 'float' object is not subscriptable
