Titlebook: Analysis of Symbolic Data; Exploratory Methods Hans-Hermann Bock,Edwin Diday Conference proceedings 2000 Springer-Verlag Berlin Heidelberg

Hypothesis

書目名稱Analysis of Symbolic Data影響因子(影響力)




書目名稱Analysis of Symbolic Data影響因子(影響力)學科排名




書目名稱Analysis of Symbolic Data網(wǎng)絡(luò)公開度




書目名稱Analysis of Symbolic Data網(wǎng)絡(luò)公開度學科排名




書目名稱Analysis of Symbolic Data被引頻次




書目名稱Analysis of Symbolic Data被引頻次學科排名




書目名稱Analysis of Symbolic Data年度引用




書目名稱Analysis of Symbolic Data年度引用學科排名




書目名稱Analysis of Symbolic Data讀者反饋




書目名稱Analysis of Symbolic Data讀者反饋學科排名

遺產(chǎn)

condone

幻想

Lars Holtkamp,Nils Arne Brockmannmplex type of data which we call . as they contain . and they are . In this context, we have a rapidly increasing need to extend standard data analysis methods (exploratory, graphical representations, clustering, factorial analysis, discrimination,…) to these symbolic data.

刺激

Assignment

https://doi.org/10.1007/978-3-322-80430-3se similarities as their data input. For example, in cluster analysis where we look for ‘homogeneous’ classes ., .,… of objects, it is typically required that pairs of objects from the . class have a . similarity (i.e., a . dissimilarity) and, conversely, that the similarity is . for pairs of objects from. classes (see Section 11.1).

匯總

calamity

Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective,mplex type of data which we call . as they contain . and they are . In this context, we have a rapidly increasing need to extend standard data analysis methods (exploratory, graphical representations, clustering, factorial analysis, discrimination,…) to these symbolic data.

中和

壯觀的游行

Similarity and Dissimilarity,se similarities as their data input. For example, in cluster analysis where we look for ‘homogeneous’ classes ., .,… of objects, it is typically required that pairs of objects from the . class have a . similarity (i.e., a . dissimilarity) and, conversely, that the similarity is . for pairs of objects from. classes (see Section 11.1).