Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data

Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the data correspond to data stream is data stream mining. In this paper, we propose the feature selection with online decision tree. At first, we construct online type decision tree to regard credit card transaction data as data stream on data stream mining. At second, we select attributes thought to be important for detection of illegal use. We apply VFDT (Very Fast Decision Tree learner) algorithm to online type decision tree construction

青年期における絶望感と死に対する態度の関係について

青年期はイニシエーションによって例えられるほど死が身近となる時期である。また,この時期は絶望感が身近な感情となる時期でもある。しかし,死という究極的な自己否定を受け入れられた青年は絶望に陥りにくいのではないだろうか。そこで本研究では大学生を対象に,絶望感尺度と死に対する尺度を用いて調査した。その結果,死に対する態度尺度からは「死に対する恐怖感」「死の肯定的評価」「生の否定的評価」「死への無関心」の4因子が抽出された。またこれらを独立変数とする重回帰分析の結果,死を積極的に受け入れるほど絶望感は低くなるが,生死のうち生に焦点を当てて否定する態度に留まるほど絶望感はむしろ高くなることが明らかとなった

Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data

Abstract-Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the data correspond to data stream is data stream mining. In this paper, we propose the feature selection with online decision tree. At first, we construct online type decision tree to regard credit card transaction data as data stream on data stream mining. At second, we select attributes thought to be important for detection of illegal use. We apply VFDT (Very Fast Decision Tree learner) algorithm to online type decision tree construction