[Published online Journal of Computer Chemistry, Japan Vol.19, A21-A24, by J-STAGE]
<Title:> 種々の科学データにおける機械学習を用いた分析の試み
<Author(s):> 奥脇 弘次, 増田 淳希, 柿沼 紗也果, 谷川 貴一, 水野 寛哉, 満野 仁美, 伊藤 雅仁, 藤方 玲衣, 望月 祐志
<Corresponding author E-Mill:> okuwaki(at)rikkyo.ac.jp
<Abstract:> In recent years, there has been progress in the development of machine learning and deep learning technologies in various fields, and a number of software packages have been released that can be implemented. Our research group has attempted to establish analysis methods using machine learning for various scientific data. In this paper, we will report on further developments such as prediction of lipophilicity of molecules, analysis of psalms data using natural language processing, and similarity calculation system of spectrum data.
<Keywords:>
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0018/_article/-char/ja/
<Title:> 種々の科学データにおける機械学習を用いた分析の試み
<Author(s):> 奥脇 弘次, 増田 淳希, 柿沼 紗也果, 谷川 貴一, 水野 寛哉, 満野 仁美, 伊藤 雅仁, 藤方 玲衣, 望月 祐志
<Corresponding author E-Mill:> okuwaki(at)rikkyo.ac.jp
<Abstract:> In recent years, there has been progress in the development of machine learning and deep learning technologies in various fields, and a number of software packages have been released that can be implemented. Our research group has attempted to establish analysis methods using machine learning for various scientific data. In this paper, we will report on further developments such as prediction of lipophilicity of molecules, analysis of psalms data using natural language processing, and similarity calculation system of spectrum data.
<Keywords:>
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0018/_article/-char/ja/
