July 2017
Intermediate to advanced
254 pages
6h 29m
English
Content preview from Mastering Machine Learning with scikit-learn - Second Edition
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Maximum margin classification and support vectors
The following figure depicts instances from two linearly separable classes and three possible decision boundaries. All of the decision boundaries separate the training instances of the positive class from the training instances of the negative class, and a perceptron can learn any of them. Which of these decision boundaries is most likely to perform best on test data?
From this visualization, it is intuitive that the dotted decision boundary is the best. The solid decision boundary is near many of the positive instances. The test set could contain a positive instance that has a slightly smaller ...
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