Simple implementation of a Support Vector Classification using the Sequential Minimal Optimization (SMO) algorithm for training.
- Python 2.7
- Python 3.4
- Numpy
Setup model (following parameters are default)
from SVCSMO import SVCSMO
model = SVCSMO(max_iter=10000, kernel_type='linear', C=1.0, epsilon=0.001)
Train model
model.fit(X, y)
Predict new observations
y_hat = model.predict(X_test)