SVM-w-SMO
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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)