A Gradient-Based Boosting Algorithm for Regression Problems
Zemel, Richard S., Pitassi, Toniann
–Neural Information Processing Systems
Adaptive boosting methods are simple modular algorithms that operate as follows. Let 9: X -t Y be the function to be learned, where the label set Y is finite, typically binary-valued.The algorithm uses a learning procedure, which has access to n training examples, {(Xl, Y1), ..., (xn, Yn)}, drawn randomly from X x Yaccording todistribution D; it outputs a hypothesis I:
Neural Information Processing Systems
Dec-31-2001