edu.stanford.nlp.optimization

## Class HybridMinimizer

• All Implemented Interfaces:
HasEvaluators, Minimizer<DiffFunction>

```public class HybridMinimizer
extends Object
implements Minimizer<DiffFunction>, HasEvaluators```
Hybrid Minimizer is set up as a combination of two minimizers. The first minimizer will ideally quickly converge regardless of proximity to the true minimum, while the second minimizer would generally be a quadratic method, that is only fully quadratic near the solution. If you read this, send me an e-mail saying, "Alex! You should finish adding the description to the Hybrid Minimizer!"
Since:
1.0
Version:
1.0
Author:
Alex Kleeman
• ### Constructor Summary

Constructors
Constructor and Description
```HybridMinimizer(Minimizer<DiffFunction> minimizerOne, Minimizer<DiffFunction> minimizerTwo, int iterationCutoff)```
• ### Method Summary

All Methods
Modifier and Type Method and Description
`double[]` ```minimize(DiffFunction function, double functionTolerance, double[] initial)```
Attempts to find an unconstrained minimum of the objective `function` starting at `initial`, accurate to within `functionTolerance` (normally implemented as a multiplier of the range value to give range tolerance).
`double[]` ```minimize(DiffFunction function, double functionTolerance, double[] initial, int maxIterations)```
Attempts to find an unconstrained minimum of the objective `function` starting at `initial`, accurate to within `functionTolerance` (normally implemented as a multiplier of the range value to give range tolerance), but running only for at most `maxIterations` iterations.
`void` ```setEvaluators(int iters, Evaluator[] evaluators)```
• ### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Constructor Detail

• #### HybridMinimizer

```public HybridMinimizer(Minimizer<DiffFunction> minimizerOne,
Minimizer<DiffFunction> minimizerTwo,
int iterationCutoff)```
• ### Method Detail

• #### setEvaluators

```public void setEvaluators(int iters,
Evaluator[] evaluators)```
Specified by:
`setEvaluators` in interface `HasEvaluators`
• #### minimize

```public double[] minimize(DiffFunction function,
double functionTolerance,
double[] initial)```
Attempts to find an unconstrained minimum of the objective `function` starting at `initial`, accurate to within `functionTolerance` (normally implemented as a multiplier of the range value to give range tolerance).
Specified by:
`minimize` in interface `Minimizer<DiffFunction>`
Parameters:
`function` - The objective function
`functionTolerance` - A `double` value
`initial` - An initial feasible point
Returns:
Unconstrained minimum of function
• #### minimize

```public double[] minimize(DiffFunction function,
double functionTolerance,
double[] initial,
int maxIterations)```
Attempts to find an unconstrained minimum of the objective `function` starting at `initial`, accurate to within `functionTolerance` (normally implemented as a multiplier of the range value to give range tolerance), but running only for at most `maxIterations` iterations.
Specified by:
`minimize` in interface `Minimizer<DiffFunction>`
Parameters:
`function` - The objective function
`functionTolerance` - A `double` value
`initial` - An initial feasible point
`maxIterations` - Maximum number of iterations
Returns:
Unconstrained minimum of function

Stanford NLP Group