{'fraction_non_alphanumeric': 0.02385685884691849, 'fraction_numerical': 0.005964214711729622, 'mean_word_length': 4.793103448275862, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Walmart Sale Forecasting Model Based On LightGBM

Accurate sales forecasts can help businesses make reasonable sales plans. In this paper, I am going to build a model for sales forecasting. First, I need to preprocess the historical data, find the obvious feature structure in the data, and eliminate the unreasonable data. I propose a GBDT-based LightGBM model, the Root Mean Square Error of this model is 2.09, which shows better predictive ability compared with linear regression model and SVM model.