The FanChenLinQuadraticOptimization type exposes the following members.
Gets the number of variables (free parameters) in the optimization problem. In a SVM learning problem, this is the number of samples in the learning dataset.
Gets the threshold (bias) value for a SVM trained using this method.
Gets or sets a value indicating whether shrinking heuristics should be used. Default is false.
Gets the current solution found, the values of the parameters which optimizes the function.
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
Gets or sets the precision tolerance before the method stops. Default is 0.001.
Gets the upper bounds for the optimization problem. In a SVM learning problem, this would be the capacity limit for each Lagrange multiplier (alpha) in the machine. The default is to use a vector filled with 1's.
Gets the output of the function at the current Solution.