Classification with neural networks with quadratic decision functions
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866909230873706496 |
|---|---|
| author | Frischauf, Leon Scherzer, Otmar Shi, Cong |
| author_facet | Frischauf, Leon Scherzer, Otmar Shi, Cong |
| contents | Neural networks with quadratic decision functions have been introduced as alternatives to standard neural networks with affine linear ones. They are advantageous when the objects or classes to be identified are compact and of basic geometries like circles, ellipses etc. In this paper we investigate the use of such ansatz functions for classification. In particular we test and compare the algorithm on the MNIST dataset for classification of handwritten digits and for classification of subspecies. We also show, that the implementation can be based on the neural network structure in the software Tensorflow and Keras, respectively. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_10710 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Classification with neural networks with quadratic decision functions Frischauf, Leon Scherzer, Otmar Shi, Cong Machine Learning Numerical Analysis 49N45, 41A30, 65XX, 68TXX Neural networks with quadratic decision functions have been introduced as alternatives to standard neural networks with affine linear ones. They are advantageous when the objects or classes to be identified are compact and of basic geometries like circles, ellipses etc. In this paper we investigate the use of such ansatz functions for classification. In particular we test and compare the algorithm on the MNIST dataset for classification of handwritten digits and for classification of subspecies. We also show, that the implementation can be based on the neural network structure in the software Tensorflow and Keras, respectively. |
| title | Classification with neural networks with quadratic decision functions |
| topic | Machine Learning Numerical Analysis 49N45, 41A30, 65XX, 68TXX |
| url | https://arxiv.org/abs/2401.10710 |