# TSVMs

A collection of Twin Support Vector Machine (TSVM) implementations for pattern classification.

## Implementations

- **TSVM** - Twin Support Vector Machine
- **UTSVM** - Unsupervised Twin Support Vector Machine
- **DTSVM** - Deep Twin Support Vector Machine
- **LSTSVM** - Least Squares Twin Support Vector Machine
- **DLSTSVM** - Deep Least Squares Twin Support Vector Machine
- **RUTSVM** - Robust Unsupervised Twin Support Vector Machine
- **RULSTSVM** - Robust Unsupervised Least Squares Twin Support Vector Machine

## Usage

Each implementation follows a similar interface:

```python
from TSVM import TSVM

# Prepare your data
# X: features (n_samples, n_features)
# y: labels (n_samples, 1) with values +1 or -1
# C1, C2: regularization parameters

# Create and train the model
model = TSVM(X, y, C1=1.0, C2=1.0)
model.fit()

# Make predictions
model.predict(x_test)
predictions = model.get_preds()
```

## Requirements

- numpy
- cvxopt

## References

- TSVM: [IEEE Paper](https://ieeexplore.ieee.org/document/4135685)
- UTSVM: [ScienceDirect](https://www.sciencedirect.com/science/article/abs/pii/S0893608012002304)
- DTSVM: [IEEE Paper](https://ieeexplore.ieee.org/abstract/document/7022580)
- LSTSVM: [ScienceDirect](https://www.sciencedirect.com/science/article/abs/pii/S0957417408006854)
- RUTSVM: [ScienceDirect](https://www.sciencedirect.com/science/article/abs/pii/S0031320319304510)

## Author

Saeed Khosravi