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Hiroshi Yadohisa
Hiroshi Yadohisa
Geverifieerd e-mailadres voor mail.doshisha.ac.jp
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Jaar
Crisp and fuzzy k-means clustering algorithms for multivariate functional data
S Tokushige, H Yadohisa, K Inada
Computational Statistics 22, 1-16, 2007
1062007
Data analysis of asymmetric structures: advanced approaches in computational statistics
T Saito, H Yadohisa
CRC Press, 2004
712004
Asymmetric agglomerative hierarchical clustering algorithms and their evaluations
A Takeuchi, T Saito, H Yadohisa
Journal of Classification 24 (1), 123-143, 2007
342007
Software development productivity of Japanese enterprise applications
M Tsunoda, A Monden, H Yadohisa, N Kikuchi, K Matsumoto
Information Technology and Management 10, 193-205, 2009
282009
Effect of Data Standardization on the Result of k-Means Clustering
K Tanioka, H Yadohisa
Challenges at the Interface of Data Analysis, Computer Science, and …, 2012
262012
Supply chain management and organizational performance: the resonant influence
BAT Duong, HQ Truong, M Sameiro, P Sampaio, AC Fernandes, ...
International Journal of Quality & Reliability Management 36 (7), 1053-1077, 2019
252019
Reduced -means clustering with MCA in a low-dimensional space
M Mitsuhiro, H Yadohisa
Computational Statistics 30 (2), 463-475, 2015
172015
Data-oriented learning system of statistics based on analysis scenario/story (DoLStat)
Y Mori, Y Yamamoto, H Yadohisa
Bulletin of the International Statistical Institute, 54th Session …, 2003
162003
Non-hierarchical clustering for distribution-valued data
Y Terada, H Yadohisa
Proceedings of COMPSTAT, 1653-1660, 2010
142010
Revealing changes in brain functional networks caused by focused-attention meditation using Tucker3 clustering
T Miyoshi, K Tanioka, S Yamamoto, H Yadohisa, T Hiroyasu, S Hiwa
Frontiers in Human Neuroscience 13, 473, 2020
132020
Productivity analysis of Japanese enterprise software development projects
M Tsunoda, A Monden, H Yadohisa, N Kikuchi, K Matsumoto
Proceedings of the 2006 international workshop on Mining software …, 2006
132006
Formulation of asymmetric agglomerative hierarchical clustering and graphical representation of its results
H Yadohisa
Bulletin of the Computational Statistics of Japan,(15), 309-316, 2002
132002
8. Functional Data Analysis DISSIMILARITY AND RELATED METHODS FOR FUNCTIONAL DATA
S Tokushige, K Inada, H Yadohisa
Journal of the Japanese Society of Computational Statistics 15 (2), 319-326, 2003
102003
Clustering preference data in the presence of response‐style bias
M Takagishi, M van de Velden, H Yadohisa
British Journal of Mathematical and Statistical Psychology 72 (3), 401-425, 2019
92019
A non-negative matrix factorization model based on the zero-inflated Tweedie distribution
H Abe, H Yadohisa
Computational Statistics 32 (2), 475-499, 2017
92017
Developing Criteria for Measuring Space Distortion in Combinatorial Cluster Analysis and Methods for Controlling the Distortion.
H Yadohisa, A Takeuchi, K Inada
Journal of Classification 16 (1), 1999
91999
An estimation of causal structure based on Latent LiNGAM for mixed data
M Yamayoshi, J Tsuchida, H Yadohisa
Behaviormetrika 47, 105-121, 2020
82020
Correspondence analysis for symbolic contingency tables based on interval algebra
I Takagi, H Yadohisa
Procedia Computer Science 6, 352-357, 2011
72011
Vector field representation of asymmetric proximity data
H Yadohisa, N Niki
Communications in Statistics-Theory and Methods 28 (1), 35-48, 1999
71999
Orthogonal nonnegative matrix tri-factorization based on Tweedie distributions
H Abe, H Yadohisa
Advances in Data Analysis and Classification 13 (4), 825-853, 2019
62019
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Artikelen 1–20