def searchForBestAntecedent(self,example,clas): ruleInstance=Rule( ) ruleInstance.setTwoParameters(self.n_variables, self.compatibilityType) print("In searchForBestAntecedent ,self.n_variables is :" + str(self.n_variables)) ruleInstance.setClass(clas) print("In searchForBestAntecedent ,self.n_labels is :" + str(self.n_labels)) for i in range( 0,self.n_variables): max = 0.0 etq = -1 per= None for j in range( 0, self.n_labels) : print("Inside the second loop of searchForBestAntecedent......") per = self.dataBase.membershipFunction(i, j, example[i]) if (per > max) : max = per etq = j if (max == 0.0) : print("There was an Error while searching for the antecedent of the rule") print("Example: ") for j in range(0,self.n_variables): print(example[j] + "\t") print("Variable " + str(i)) exit(1) ruleInstance.antecedent[i] = self.dataBase.clone(i, etq) return ruleInstance
def searchForBestAntecedent(self, example, clas): ruleInstance = Rule() ruleInstance.setTwoParameters(self.n_variables, self.compatibilityType) # print("In searchForBestAntecedent ,self.n_variables is :" + str(self.n_variables)) ruleInstance.setClass(clas) # print("In searchForBestAntecedent ,self.n_labels is :" + str(self.n_labels)) example_feature_array = [] for f_variable in range(0, self.n_variables): # print("The f_variable is :"+str(f_variable)) # print("The example is :" + str(example)) example_feature_array.append(example[f_variable]) label_array = [] for i in range(0, self.n_variables): max_value = 0.0 etq = -1 per = None for j in range(0, self.n_labels): # print("Inside the second loop of searchForBestAntecedent......") per = self.dataBase.membershipFunction(i, j, example[i]) if per > max_value: max_value = per etq = j if max_value == 0.0: # print("There was an Error while searching for the antecedent of the rule") # print("Example: ") for j in range(0, self.n_variables): print(example[j] + "\t") print("Variable " + str(i)) exit(1) # print(" The max_value is : " + str(max_value)) # print(" ,the j value is : " + str(j)) ruleInstance.antecedent[i] = self.dataBase.clone( i, etq) # self.dataBase[i][j] label_array.append(etq) data_row_temp = data_row() data_row_temp.set_three_parameters(clas, example_feature_array, label_array) ruleInstance.data_row_here = data_row_temp return ruleInstance