Developer Guide

Contents

SAMME method

Training Stage

The following scheme shows the major steps of the SAMME algorithm:
  1. Initialize weights
    for
    i
    = 1, ...,
    n
    .
  2. For
    t
    = 1, ...,
    T
    :
    1. Train the weak learner
      using weights
      D
      t
      .
    2. Choose a confidence value
      where
    3. Update
      , where
      Z
      t
      is a normalization factor.
  3. Output the final hypothesis:
SAMME algorithm in case of binary classification is equal to the AdaBoost algorithm from [Friedman98]

Prediction Stage

Given the AdaBoost classifier and
r
feature vectors
x
1
, ...,
x
r
, the problem is to calculate the final class
H
(
x
):

Product and Performance Information

1

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Notice revision #20110804