Research on Wordle based on ARIMA and GBDT models
DOI:
https://doi.org/10.54097/7z3shj22Keywords:
AMIRA time series model, Gradient Boosting, Decision Tree (GBDT) model.Abstract
Wordle is a very popular word guessing at the moment, where players have a total of six chances to guess a five-letter word. Based on the AMIRA time series model, this paper analyzes the data and predicts the changes in the number of people who submit reports in the future, and then analyzes the word attributes that affect the accuracy of word guessing according to a large number of actual data, and establishes a Gradient Boosting Decision Tree (GBDT) model according to the determined word attributes to predict the correct guess rate of any word, and finally predicts and analyzes the word "EERIE".
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NetEase: Anagram Wordle is now available on The New York Times' Crossword app. https: //www.163.com/dy/article/HFK1MKQ90511BLFD.html.
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