紀要論文 機械学習アルゴリズムを用いた防衛白書の計量分析
Quantitative Analysis of Japan’s Defense White Paper Using a Machine Learning Algorithm
キカイ ガクシュウ アルゴリズム ヲ モチイタ ボウエイ ハクショ ノ ケイリョウ ブンセキ

河合, 将志  ,  Kawai, Masashi  ,  カワイ, マサシ

22 ( 1 )  , pp.65 - 72 , 2017-09 , 大阪大学大学院国際公共政策研究科 , オオサカ ダイガク ダイガクイン コクサイ コウキョウ セイサク ケンキュウカ
ISSN:2432-0870
NII書誌ID(NCID):AA1115271X
内容記述
In Honor of Prof. Toshitaka TAKEUCHI
竹内俊隆教授退職記念論文集
Is there a newly formed concept interpretable as a basis for Japan’s security policy that has been becoming prominent since the Gulf War? This study empirically examines this question without focusing on specific concepts such as the “Dynamic Defense Force” and the “Dynamic Joint Defense Force” recently introduced by Japan’s Ministry of Defense. By primarily applying random forest, a machine learning algorithm, to the Defense White Papers published by the Ministry between 1970 and 2016, the present author finds it difficult to identify such a concept.
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http://ir.library.osaka-u.ac.jp/repo/ouka/all/65094/osipp_041_065.pdf

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