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package edu.stanford.nlp.optimization;

/**
 * The interface for unconstrained function minimizers.
 * 

* Implementations may also vary in their requirements for the * arguments. For example, implementations may or may not care if the * initial feasible vector turns out to be non-feasible * (or null!). Similarly, some methods may insist that objectives * and/or constraint Function objects actually be * DiffFunction objects. * * @author Dan Klein * @version 1.0 * @since 1.0 */ public interface Minimizer { /** * Attempts to find an unconstrained minimum of the objective * function starting at initial, within * functionTolerance. * * @param function the objective function * @param functionTolerance a double value * @param initial a initial feasible point * @return Unconstrained minimum of function */ double[] minimize(T function, double functionTolerance, double[] initial); double[] minimize(T function, double functionTolerance, double[] initial, int maxIterations); }





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