opennlp.tools.ml.maxent.quasinewton

## Class QNMinimizer

- java.lang.Object
- - opennlp.tools.ml.maxent.quasinewton.QNMinimizer

-     public class QNMinimizer
      extends Object

  Implementation of L-BFGS which supports L1-, L2-regularization and Elastic Net for solving convex optimization problems.

  Usage example:

  >       // Quadratic function f(x) = (x-1)^2 + 10
  >       // f obtains its minimum value 10 at x = 1
  >       Function f = new Function() {

  >          @Override
  >         public int getDimension() {
  >           return 1;
  >         }

  >          @Override
  >         public double valueAt(double[] x) {
  >           return StrictMath.pow(x[0]-1, 2) + 10;
  >         }

  >          @Override
  >         public double[] gradientAt(double[] x) {
  >           return new double[] { 2*(x[0]-1) };
  >         }

  >       };

  >       QNMinimizer minimizer = new QNMinimizer();
  >       double[] x = minimizer.minimize(f);
  >       double min = f.valueAt(x);

- - ### Nested Class Summary

    Nested Classes
    Modifier and Type | Class and Description
    --- | ---
    `static interface` | `QNMinimizer.Evaluator` Evaluate quality of training parameters.
    `static class` | `QNMinimizer.L2RegFunction` L2-regularized objective function

  - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static double` | `CONVERGE_TOLERANCE`
    `static double` | `INITIAL_STEP_SIZE`
    `static double` | `L1COST_DEFAULT`
    `static double` | `L2COST_DEFAULT`
    `static int` | `M_DEFAULT`
    `static int` | `MAX_FCT_EVAL_DEFAULT`
    `static double` | `MIN_STEP_SIZE`
    `static int` | `NUM_ITERATIONS_DEFAULT`
    `static double` | `REL_GRAD_NORM_TOL`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `QNMinimizer()`
    `QNMinimizer(double l1Cost, double l2Cost)`
    `QNMinimizer(double l1Cost, double l2Cost, int iterations)`
    `QNMinimizer(double l1Cost, double l2Cost, int iterations, int m, int maxFctEval)`
    `QNMinimizer(double l1Cost, double l2Cost, int iterations, int m, int maxFctEval, boolean verbose)` Constructor

  - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `QNMinimizer.Evaluator` | `getEvaluator()`
    `double[]` | `minimize(Function function)` Find the parameters that minimize the objective function
    `void` | `setEvaluator(QNMinimizer.Evaluator evaluator)`

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Field Detail

    - #### CONVERGE_TOLERANCE

          public static final double CONVERGE_TOLERANCE

      See Also:
        Constant Field Values

    - #### REL_GRAD_NORM_TOL

          public static final double REL_GRAD_NORM_TOL

      See Also:
        Constant Field Values

    - #### INITIAL_STEP_SIZE

          public static final double INITIAL_STEP_SIZE

      See Also:
        Constant Field Values

    - #### MIN_STEP_SIZE

          public static final double MIN_STEP_SIZE

      See Also:
        Constant Field Values

    - #### L1COST_DEFAULT

          public static final double L1COST_DEFAULT

      See Also:
        Constant Field Values

    - #### L2COST_DEFAULT

          public static final double L2COST_DEFAULT

      See Also:
        Constant Field Values

    - #### NUM_ITERATIONS_DEFAULT

          public static final int NUM_ITERATIONS_DEFAULT

      See Also:
        Constant Field Values

    - #### M_DEFAULT

          public static final int M_DEFAULT

      See Also:
        Constant Field Values

    - #### MAX_FCT_EVAL_DEFAULT

          public static final int MAX_FCT_EVAL_DEFAULT

      See Also:
        Constant Field Values

  - ### Constructor Detail

    - #### QNMinimizer

          public QNMinimizer()

    - #### QNMinimizer

          public QNMinimizer(double l1Cost,
                             double l2Cost)

    - #### QNMinimizer

          public QNMinimizer(double l1Cost,
                             double l2Cost,
                             int iterations)

    - #### QNMinimizer

          public QNMinimizer(double l1Cost,
                             double l2Cost,
                             int iterations,
                             int m,
                             int maxFctEval)

    - #### QNMinimizer

          public QNMinimizer(double l1Cost,
                             double l2Cost,
                             int iterations,
                             int m,
                             int maxFctEval,
                             boolean verbose)

      Constructor
      Parameters:
        `l1Cost` - L1-regularization cost
        `l2Cost` - L2-regularization cost
        `iterations` - maximum number of iterations
        `m` - number of Hessian updates to store
        `maxFctEval` - maximum number of function evaluations
        `verbose` - verbose output

  - ### Method Detail

    - #### getEvaluator

          public QNMinimizer.Evaluator getEvaluator()

    - #### setEvaluator

          public void setEvaluator(QNMinimizer.Evaluator evaluator)

    - #### minimize

          public double[] minimize(Function function)

      Find the parameters that minimize the objective function
      Parameters:
        `function` - objective function
      Returns:
        minimizing parameters

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