Name
Abstract | ||
|---|---|---|
A classification function maps a set of vectors into several classes. A machine learning problem is treated as a design problem for partially defined classification functions. To realize classification functions forMNIST hand written digits, three different architectures are considered: Single-unit realization, 45-unit realization, and 45-unit xr realization. The 45-unit realization consists of 45 ternary classifiers, 10 counters, and a max selector. Test accuracy of these architectures are compared using MNIST data set. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1587/transinf.2020LOP0002 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | DocType | Volume |
linear decomposition, partially defined function, support minimization, classification, digit recognition, MNIST, index generation function, machine learning, neural network, ensemble method | Journal | E104D |
Issue | ISSN | Citations |
8 | 1745-1361 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tsutomu Sasao | 1 | 1083 | 141.62 |
| Yuto Horikawa | 2 | 0 | 0.34 |
| yukihiro iguchi | 3 | 85 | 13.24 |