Method predict

supervised_class2/adaboost.py:40–47

(self, X)

      self.alphas.append(alpha)

  def predict(self, X):
    # NOT like SKLearn API
    # we want accuracy and exponential loss for plotting purposes
    N, _ = X.shape
    FX = np.zeros(N)
    for alpha, tree in zip(self.alphas, self.models):
      FX += alpha*tree.predict(X)
    return np.sign(FX), FX

  def score(self, X, Y):
    # NOT like SKLearn API