def fit(x,y, lrate): cost_ = [] n_iterations_ = [] w_ = np.zeros((x.shape[1], 1)) m = x.shape[0] n_iterations = 10 i = 0 while i < n_iterations: y_pred = np.dot(x, w_) residuals = y_pred - y gradient_vector = np.dot(x.T, residuals) w_ -= (lrate / m) * gradient_vector *(-2) cost = np.sum((residuals ** 2)) / m cost_.append(cost) n_iterations_.append(i) i+=1 return w_, cost_, n_iterations_learning_rates = [1E-6, 1E-5, 1E-4, 1E-3, 1E-2, 1E-1]for i in range(len(learning_rates)): lr = fit(X_train, y_train,learning_rates[i]) print(lr[1])当我运行上述代码时，得到以下输出
[576.1537376237624, 576.1545609827812, 576.155384359385, 576.1562077535746, 576.1570311653502, 576.1578545947123, 576.1586780416611, 576.1595015061973, 576.1603249883211, 576.1611484880332][576.1537376237624, 576.161971609612, 576.1702073541688, 576.1784448578509, 576.1866841210765, 576.1949251442638, 576.2031679278315, 576.2114124721976, 576.219658777781, 576.2279068450003][576.1537376237624, 576.2361170484683, 576.3186725320611, 576.4014044933067, 576.48431335199, 576.5673995289181, 576.6506634459224, 576.7341055258611, 576.8177261926215, 576.9015258711238][576.1537376237624, 576.9814884918198, 577.8270339789372, 578.6907997611174, 579.5732219342204, 580.4747472702393, 581.3958334798867, 582.3369494816455, 583.2985756774436, 584.281204235115][576.1537376237624, 584.826908404254, 595.4739343028948, 608.5938411910076, 624.8145782295895, 644.9264682232412, 669.9243443735022, 701.0606295042115, 739.9121998096105, 788.4646133533605][576.1537376237624, 702.4516554203875, 1277.1568412503211, 4042.0736136112046, 17595.436653069664, 84433.45249482371, 414672.7920504886, 2047336.072196413, 10120573.694524828, 50043771.857434966]我想从输出中访问各个列表，我的期望输出是
[576.1537376237624, 576.1545609827812, 576.155384359385, 576.1562077535746, 576.1570311653502, 576.1578545947123, 576.1586780416611, 576.1595015061973, 576.1603249883211, 576.1611484880332]回答：
learning_rates = [1E-6, 1E-5, 1E-4, 1E-3, 1E-2, 1E-1]all_results=[]for i in range(len(learning_rates)): lr = fit(X_train, y_train,learning_rates[i]) all_results.append(lr[0])然后：
for i in range(len(all_results)): print(all_results[i]) # 逐行打印