recall theory of learning 中文意思是什麼
recall theory of learning
解釋
學習的理論回憶說-
Because of ineffectiveness of naive bayes model for text classification, this thesis proposed integrating boosting theory of machine learning in classification process, boost naive bayes categorization model through many times training. improved by experiments, mutual information and naive bayes integrated with boosting bring very good precision, recall, and f1 score
鑒于樸素貝葉斯的分類效果不佳,本論文又提出將機器學習中的boosting思想結合到樸素貝葉斯的分類模型中,對樸素貝葉斯模型進行提升,實驗證明,改進的互信息和給合了boosting思想的樸素貝葉斯分類模型均產生良好的分類效果?分準率、分全率及f1值。
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