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Journal Articles
- 2017
[j2]Natsuki Sano, Tomomichi Suzuki:
Efficient hyper parameter selection for support vector regression using orthogonal array. Int. J. Comput. Intell. Stud. 6(1): 40-51 (2017)- [j1]Natsuki Sano, Yuki Mori, Tomomichi Suzuki:
Defect Detection Using Unanimous Vote Among Mahalanobis Classifiers for Each Color Component. Rev. Socionetwork Strateg. 11(2): 173-183 (2017)
Conference and Workshop Papers
- 2024
- [c9]Natsuki Sano
, Katsutoshi Yada, Shunsuke Okamoto, Tomomichi Suzuki:
Evaluation of sales areas in supermarket by Markov chain model. MISNC 2024: 50-54 - 2018
- [c8]Rina Tanaka, Aya Ishigaki, Tomomichi Suzuki, Masato Hamada, Wataru Kawai:
Shipping Plan for Apparel Products Using Shipping Record and Just-in-Time Inventory at a Logistics Warehouse. IIAI-AAI 2018: 682-687 - 2016
- [c7]Natsuki Sano, Reo Tsutsui, Katsutoshi Yada, Tomomichi Suzuki:
Clustering of Customer Shopping Paths in Japanese Grocery Stores. KES 2016: 1314-1322 - [c6]Natsuki Sano, Yuki Mori, Tomomichi Suzuki:
Defect detection using two-dimensional moving range filter and unanimous vote among color component classifiers. MISNC 2016: 11 - 2015
- [c5]Natsuki Sano, Natsumi Machino, Katsutoshi Yada, Tomomichi Suzuki:
Recommendation System for Grocery Store Considering Data Sparsity. KES 2015: 1406-1413 - 2014
- [c4]Natsuki Sano, Katsutoshi Yada, Tomomichi Suzuki:
Category evaluation method for business intelligence using a hierarchical Bayes model. ICCI*CC 2014: 400-407 - [c3]Natsuki Sano, Syusuke Tamura, Katsutoshi Yada, Tomomichi Suzuki:
Evaluation of Price Elasticity and Brand Loyalty in Milk Products. KES 2014: 1482-1487 - [c2]Natsuki Sano, Kaori Higashinaka, Tomomichi Suzuki:
Efficient parameter selection for Support Vector Regression using orthogonal array. SMC 2014: 2256-2261 - 2013
- [c1]Natsuki Sano, Tomomichi Suzuki:
Evaluation of Discount Effects Using Poisson Regression Based on Interaction Effects between Bargain Scale and Product Category. ICDM Workshops 2013: 234-241
Coauthor Index
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