我在使用SMO算法时遇到了一个错误，提示’float’对象不能被解释为整数。由于我是Python新手，所以感到很困惑，请帮帮我…
class SMO(): def __init__(self,regularization_nn,learning_rate_RBM,learning_rate_nn,n_iter_RBM,batch_size_RBM,batch_size_nn,n_iter_nn): self.learning_rate_RBM=0.006 self.learning_rate_nn=0.1 self.n_iter_RBM=20 self.batch_size_RBM=100 self.batch_size_nn=100 self.n_iter_nn=5000 self.PopSize=batch_size_RBM self.dim=n_iter_RBM self.acc_err=batch_size_nn self.lb=learning_rate_RBM self.ub=learning_rate_nn self.objf=regularization_nn self.pos=numpy.zeros((batch_size_RBM,n_iter_RBM)) self.fun_val = numpy.zeros(batch_size_RBM) self.fitness = numpy.zeros(batch_size_RBM) self.gpoint = numpy.zeros((batch_size_RBM,2)) self.prob=numpy.zeros(batch_size_RBM) self.LocalLimit=n_iter_RBM*batch_size_RBM; self.GlobalLimit=batch_size_RBM; self.fit = numpy.zeros(batch_size_RBM) self.MinCost=numpy.zeros(n_iter_nn) self.Bestpos=numpy.zeros(n_iter_RBM) def initialize(self):global GlobalMin, GlobalLeaderPosition, GlobalLimitCount, LocalMin, LocalLimitCount, LocalLeaderPositionS_max=int(self.PopSize/2)LocalMin = numpy.zeros(S_max)LocalLeaderPosition=numpy.zeros((S_max,self.dim))LocalLimitCount=numpy.zeros(S_max)for i in range(self.PopSize): print(i) for j in range(self.dim): if type(self.ub)==int: self.pos[i,j]=random.random()*(self.ub-self.lb)+self.lb else: self.pos[i,j]=random.random()*(self.ub[j]-self.lb[j])+self.lb[j]这是错误的跟踪信息：
---------------------------------------------------------------------------TypeError Traceback (most recent call last)<ipython-input-98-1b2f665e0321> in <module>() 1 if __name__ == '__main__':----> 2 chimp_optimizer(X,Y,X_train,X_test)2 frames<ipython-input-23-1b18b438af48> in chimp_optimizer(X, Y, X_train, Y_train) 16 #print(fopt) 17 ---> 18 x,succ_rate,mean_feval = main(Deep_belief_network,X,Y,regularization_nn,learning_rate_RBM,learning_rate_nn,n_iter_RBM,batch_size_RBM,batch_size_nn,n_iter_nn) 19 return x,succ_rate,mean_feval<ipython-input-97-906c6850e06b> in main(regularization_nn, learning_rate_RBM, learning_rate_nn, n_iter_RBM, batch_size_RBM, n_iter_nn, batch_size_nn, obj_val, succ_rate, mean_feval) 252 253 # =========================== Calling: initialize() =========================== #--> 254 smo.initialize() 255 256 # ========================== Calling: GlobalLearning() ======================== #<ipython-input-97-906c6850e06b> in initialize(self) 51 S_max=int(self.PopSize/2) 52 LocalMin = numpy.zeros(S_max)---> 53 LocalLeaderPosition=numpy.zeros((int(S_max),self.dim)) 54 LocalLimitCount=numpy.zeros(S_max) 55 for i in range(self.PopSize):TypeError: 'float' object cannot be interpreted as an integer我不知道为什么会出现这个错误…请指导我，我已经尝试过更改一些值但没有效果
回答：
应该使用 numpy.zeros( (int(batch_size_RBM), int(n_iter_RBM)) )
