Table 1 Test classification accuracy of the proposed HNF for different datasets using random matrices
From: High-dimensional neural feature design for layer-wise reduction of training cost
| Dataset | Size of training data | Size of testing data | Input dimension (P) | Number of classes (Q) | Proposed HNF | ELM | Proposed HNF | State-of-the-art [reference] | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Accuracy | n(1) | L | Accuracy | Accuracy | n(1) | L | ||||||
| Letter | 13,333 | 6667 | 16 | 26 | 93.3 | 250 | 5 | 88.3 | 94.6 | 1000 | 3 | 95.8 [25] |
| Shuttle | 43,500 | 14,500 | 9 | 7 | 99.3 | 250 | 5 | 99.0 | 99.6 | 1000 | 3 | 99.9 [19] |
| MNIST | 60,000 | 10,000 | 784 | 10 | 97.1 | 1000 | 5 | 96.9 | 97.7 | 4000 | 3 | 99.7 [26] |
