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研究生: 曾瓈儀
Zeng, Li-Yi
論文名稱: 以機器學習技術預測二級毒品緩起訴者甲基安非他命使用情形
Predicting Methamphetamine Use Among Deferred Prosecution Offenders of Schedule II Drugs Using Machine Learning
指導教授: 李思賢
Lee, Tony Szu-Hsien
口試委員: 李思賢
Lee, Tony Szu-Hsien
顧以謙
Ku, Yi-Chien
楊浩然
Yang, Hao-Jan
口試日期: 2025/01/03
學位類別: 碩士
Master
系所名稱: 健康促進與衛生教育學系
Department of Health Promotion and Health Education
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 85
中文關鍵詞: 機器學習二級毒品緩起訴戒癮治療決策樹隨機森林支持向量機
英文關鍵詞: Machine Learning, Schedule II Drugs, Deferred Prosecution, Addiction Treatment, Decision Tree, Random Forest, Support Vector Machine
研究方法: 次級資料分析
DOI URL: http://doi.org/10.6345/NTNU202500447
論文種類: 學術論文
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  • 摘要 i Abstract iii 目次 v 第一章 前言 1 第一節 研究背景 1 第二節 研究目的 4 第二章 文獻探討 6 第一節 毒品犯罪政策與處遇策略的實證 6 第二節 影響毒品使用行為的心理與社會因素 9 第三節 應用於醫藥衛生領域的資料探勘 12 第三章 研究方法 15 第一節 研究工具 15 第二節 研究樣本 15 第三節 研究假設 16 第四節 資料前處理 16 第五節 研究變數 17 第六節 研究設計 28 第四章 研究結果 31 第一節 原始資料集分布 31 第二節 比對過採樣資料集與原始資料集 44 第三節 模型設定 53 第四節 模型最佳性能比較 55 第五節 決策樹討論與視覺化 63 第五章 討論 70 第六章 結論 74 參考文獻 76

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