xgboost_wuyh
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The idea of our team is to use the data of the least missing December as the training set and the validation set, obtain the optimal parameters through grid search, and use the xgboost machine learning model to learn and predict the results of each month next year
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Metrics Over Time
Publication Details
Subfield
Artificial Intelligence
Field
Computer Science
Domain
Physical Sciences
Confidence Score
38%
Source
Scholar Data Model