# Supervised Linear Model-based Classification Algorithm

(Redirected from Linear Classifier)

## References

### 2011

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