Supervised Linear Model-based Classification Algorithm

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A Supervised Linear Model-based Classification Algorithm is a supervised model-based classification algorithm that fits a linear classification function.



References

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2011

  • http://en.wikipedia.org/wiki/Linear_classifier
    • … If the input feature vector to the classifier is a real vector [math]\vec x[/math], then the output score is [math]y = f(\vec{w}\cdot\vec{x}) = f\left(\sum_j w_j x_j\right),[/math] where [math]\vec w[/math] is a real vector of weights and [math]f[/math] is a function that converts the dot product of the two vectors into the desired output. (In other words, [math]\vec{w}[/math] is a one-form or linear functional mapping [math]\vec x[/math] onto R.) The weight vector [math]\vec w[/math] is learned from a set of labeled training samples. Often [math]f[/math] is a simple function that maps all values above a certain threshold to the first class and all other values to the second class. A more complex [math]f[/math] might give the probability that an item belongs to a certain class.

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