purpleboy/SVM-w-SMO

Simple implementation of a Support Vector Machine using the Sequential Minimal Optimization (SMO) algorithm for training.

SVM

Simple implementation of a Support Vector Machine using the Sequential Minimal Optimization (SMO) algorithm for training.

Supported python versions:

• Python 2.7
• Python 3.4

Python package dependencies

• Numpy (http://docs.scipy.org/doc/numpy-1.10.1/user/install.html)

Documentation

Setup model (following parameters are default)

from SVM import SVM
model = SVM(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)