Discriminative Linear Classifier Learning Algorithm

A Discriminative Linear Classifier Learning Algorithm is a discriminative learning algorithm that is a Linear Classifier Learning Algorithm.

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• Example(s):
  • a Discriminative Linear Classifier Learning with a Convex Loss Function Algorithm.
  • …
• Counter-Example(s):
  • Generative Learner.
• See: Linear SVMs, Logistic Regression.

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References

2014

• http://en.wikipedia.org/wiki/Linear_classifier#Generative_models_vs._discriminative_models
  • There are two broad classes of methods for determining the parameters of a linear classifier [math]\displaystyle{ \vec w }[/math]. …

    … The second set of methods includes discriminative models, which attempt to maximize the quality of the output on a training set. Additional terms in the training cost function can easily perform regularization of the final model. Examples of discriminative training of linear classifiers include

    • Logistic regression — maximum likelihood estimation of [math]\displaystyle{ \vec w }[/math] assuming that the observed training set was generated by a binomial model that depends on the output of the classifier.
    • Perceptron — an algorithm that attempts to fix all errors encountered in the training set
    • Support vector machine — an algorithm that maximizes the margin between the decision hyperplane and the examples in the training set.

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