Wei jian shi ji : 5 juan /

Chong kan ben.

Xu You xitang ni Ming shi yue fu : fu: Lun shi jue ju /

Double leaves, oriental style, in case.

Dong gang shi sheng : shi si juan, juan shou, juan mo /

Jiaqing er shi nian Shu Wei xu shu ji ke shu shi.

Nan gai shi gao : yi juan /

Jiaqing wu yin Zhu Dong xu shu ji Ding shi ke shu shi.

Yi an zhai shi ji : liu juan, juan shou /

Nei feng you shang: Jiaqing shi si nian juan, zuo xia: De fen hou pu cang ban.

Dan cui xuan shi cao : er juan /

Nei feng you shang: Jiaqing geng chen xin juan, zuo xia: Jiang zhou shou ju cang ban.

Quan Tang jin ti shi chao : wu juan /

Daoguang er nian Yao Wentian xu shu ji qi ke shu shi.

Lu'an shi chao qian bian : si juan ; Lu'an shi chao hou bian : shi er juan /

Nei feng you shang juan: Daoguang ji hai xin ke, zuo xia juan: Gua guo wei neng zhai cang ban.

Xi wen guo zhai wen ji : shi er juan /

Nei feng tian tou juan: Daoguang ji hai zhong qiu juan, zuo xia juan: Hou yuan tang cang ban.

Jimo shi sheng : shi er juan /

Nei feng you shang juan: Daoguang geng zi juan, zuo xia juan: Xiao xian shan fang cang ban.

Hōrei zensho.

Some issues published in parts.

Nan Yang Qun Dao xin di tu = Map of East Indies /

Insets: Zhaowa xiang tu -- Nan Yang Qun Dao di xing tu -- Malai Ban Dao xiang tu.

Using self organizing maps on compositional data

Self-organizing maps (Kohonen 1997) is a type of artificial neural network developed to explore patterns in high-dimensional multivariate data. The conventional version of the algorithm involves the use of Euclidean metric in the process of adaptation of the model vectors, thus rendering in theory a whole methodology incompatible with non-Euclidean geometries. In this contribution we explore the two main aspects of the problem: 1. Whether the conventional approach using Euclidean metric can shed valid results with compositional data. 2. If a modification of the conventional approach replacing vectorial sum and scalar multiplication by the canonical operators in the simplex (i.e. perturbation and powering) can converge to an adequate solution. Preliminary tests showed that both methodologies can be used on compositional data. However, the modified version of the algorithm performs poorer than the conventional version, in particular, when the data is pathological. Moreover, the conventional ap- proach converges faster to a solution, when data is \well-behaved". Key words: Self Organizing Map; Artificial Neural networks; Compositional data

Shina kenkyū /

Contributions by various authors.