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

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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

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)

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

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