-
Notifications
You must be signed in to change notification settings - Fork 4
Techniques included
Gustavo Rosa edited this page Feb 24, 2017
·
9 revisions
In this package, we have the following techniques:
- Standard RBMs
- Tensor RBMs
- Gaussian RBMs
- Dropout RBMs
- Dropout Gaussian RBMs
- Dropconnect RBMs
- Discriminative RBMs
- Dropout Discriminative RBMs
- Gaussian Discriminative RBMs
- Dropout Gaussian Discriminative RBMs
- Standard DBMs
- Tensor DBMs
- Dropout DBMs
- Dropconnect DBMs
- Standard DBNs
- Tensor DBNs
- Dropout DBNs
- Dropconnect DBNs
- EPNN with OPF classification and optimization
- OPF clustering with optimization
- OPF-knn with optimization
- OPF pruning with optimization
- Combinatorial OPF
- Feature Selection with OPF classification
- Feature Selection with Hamming distance
- Standard Linear Regression
- Standard Logistic Regression
All references and further information can be found at: https://github.com/jppbsi/LibOPF/wiki and https://github.com/jppbsi/LibDEEP/wiki