Why Modeling Works Even If InputData Is Different?

this is part of dataset.

def result_xgb(clf):

inputData = [20200101190000, 20200101193000]  inputData2 = np.array([inputData])    index = 1;  result_data = OrderedDict()  for x in clf.predict_proba(inputData2,ntree_limit=None, validate_features=False,base_margin=None)[0]:      result_data[transportation(index)] = round(x,2)      index += 1    print("result_name : ", max(result_data.items(), key=operator.itemgetter(1))[0])  print("result_value : ", max(clf.predict_proba(inputData2, ntree_limit=None, validate_features=False, base_margin=None)[0]))  print(result_data)  

I want to model xgboost works when I put InputData = [1900, 1930] in, but I don't understand that the result comes out even if I put InputData in 20200101190000 instead of 1900.

what's the cause?

hope for help. Thank you.

https://stackoverflow.com/questions/66947628/why-modeling-works-even-if-inputdata-is-different April 05, 2021 at 10:31AM