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A Consideration of Period for Integrated Study Required for Small Elementary School : Using a Movie Production Project as a Clue
No full textA Consideration of Period for Integrated Study Required for Small Elementary School：Using a Movie Production Project as a Clu
Studying the Bases of Non-representational Theory : The Theory on Society
No full textThis study examines the bases of non-representational theory of Nigel Thrift, which is first of all characterized by “non” against the representational theories combining such many works as Karl Marx, John Dewy and so forth, in order to make it a departing point of modern theories on society, which has to be evaluate lofty as today’s general theory
Understanding the Theory on Modern Capitalist Society Based on the Non-representational Theory
No full textThis paper engages with characteristics of the theory on the modern capitalist society presented by Nigel Thrift, in which fundamental theorems are based on the Marxian economic theories, evaluating the whole certainly so theoretically excellent, but thinking it so as a noteworthy point, that Thrift’ theoretical analysis concentrates on the commodity production today
OSS プロジェクト エ ノ オンボーディング シエン ノ タメ ノ Good First Issue ジドウ ブンルイ
No full textオープンソースソフトウェア(OSS)開発プロジェクトは，プロジェクトの持続可能性を維持するために常に新たな開発者からの貢献を求めている．一部のプロジェクトでは，「Good First Issue(GFI)」と呼ばれるラベルを用いて，新規開発者向けのIssueを用意しオンボーディングを支援している．ただし，ラベル付けはプロジェクトメンテナの手作業で行われておりメンテナにとって負担となるため，多くのプロジェクトではGFIラベルは積極的に利用されていない．本研究の目的は，OSSプロジェクトの新規開発者向けのIssueを自動分類する機械学習モデルを構築することである．本論文では，ランダムフォレストを用いて分類モデルを構築した結果を述べる．通常Issue約15万件とGFI約1万件を収集して10分割交差検証を行った結果，Precisionが0.91，Recallが0.30となった(RQ1)．また，重要度が高い特徴量を分析し，GFIの分類には投稿者のプロジェクト内での役割が重要であることが分かった(RQ2)
ラフ シュウゴウ ト ケイシキ ガイネン ブンセキ オ モチイタ ホウガン カンケイ ヘイキ ケッテイ ルールグン ヒョウキホウ ノ テイアン
No full textIn recent years, rough set theory has attracted attention as one of the data mining techniques. However, when there are tens or hundreds of decision rules extracted as a result of analysis, it is difficult to identify the combination of attribute values with high frequency of occurrence (core) and the inclusion relations among decision rules and attribute values. Therefore, the purpose of this study was to develop a notation that reflects the extraction of cores in decision rules and the inclusion relations between attributes obtained by formal concept analysis in the decision rule condition part. This enabled us to discover inclusion relations between decision rules and affinity between cores and attribute values, which were difficult to discover in rough set theory alone. We also verified the usefulness of the proposed notation by comparing the proposed notation with the conventional decision rule notation using two example problems as case studies
