|  | ## Fast Large Margin

#### Synopsis

A fast learning method for large margin optimizations.

#### Description

Applies a fast margin learner based on the linear support vector learning scheme proposed by R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Although the result is similar to those delivered by classical SVM or logistic regression implementations, this linear classifier is able to work on data set with millions of examples and attributes.

#### Input

- training set: expects: ExampleSet

#### Output

- model:
- exampleSet:

#### Parameters

- solver: The solver type for this fast margin method.
- C: The cost parameter C for c_svc, epsilon_svr, and nu_svr.
- epsilon: Tolerance of termination criterion.
- class weights: The weights w for all classes, i.e. set the parameters C of each class w * C (empty: using 1 for all classes where the weight was not defined).
- use bias: Indicates if an intercept value should be calculated.

#### ExampleProcess