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A simple classifier

A simple classifier. Ridge regression A variation on standard linear regression Adds a “ridge” term that has the effect of “smoothing” the weights Equivalent to training a linear network with weight decay. A “Strong” Classifier: SNoW– Sparse Network of Winnows.

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A simple classifier

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  1. A simple classifier • Ridge regression • A variation on standard linear regression • Adds a “ridge” term that has the effect of “smoothing” the weights • Equivalent to training a linear network with weight decay.

  2. A “Strong” Classifier:SNoW– Sparse Network of Winnows • Roth et al. 2000 – Currently best reported face detector • 1. Turn each pixel into a sparse, binary vector • 2. Activation = sign( ) • 3. Train with the Winnow update rule

  3. AdaBoost for Feature Selection • Viola and Jones (2001) used AdaBoost as a feature selection method • For each round of AdaBoost: • For each patch, train a classifier using only that one patch. • Select the best one as the classifier for this round • reweight distribution based on that classifier.

  4. Results

  5. AdaBoost consistently improves performance

  6. AdaBoost consistently improves performance

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