Data Mining: Practical Machine Learning Tools and Techniques, Second Edition

(Brent) #1

4.6 LINEAR MODELS 127


While some instances are misclassified
for every instance a
classify a using the current weights
if the predicted class is incorrect
if a belongs to the first class
for each ai that is 1, multiply wi by a
(if ai is 0, leave wi unchanged)
otherwise
for each ai that is 1, divide wi by a
(if ai is 0, leave wi unchanged)

(a)

While some instances are misclassified
for every instance a
classify a using the current weights
if the predicted class is incorrect
if a belongs to the first class
for each ai that is 1,
multiply wi+ by a
divide wi– by a
(if ai is 0, leave wi+ and wi- unchanged)
otherwise for
for each ai that is 1,
multiply wi– by a
divide wi+ by a
(if ai is 0, leave wi+ and wi- unchanged)

(b)
Figure 4.11The Winnow algorithm: (a) the unbalanced version and (b) the balanced
version.

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