SimulatedAnealingMinimizer (core 5.6.16 API)

java.lang.Object
- org.elasticsearch.search.aggregations.pipeline.movavg.SimulatedAnealingMinimizer

```
public class SimulatedAnealingMinimizer
extends java.lang.Object
```
A cost minimizer which will fit a MovAvgModel to the data. This optimizer uses naive simulated annealing. Random solutions in the problem space are generated, compared against the last period of data, and the least absolute deviation is recorded as a cost. If the new cost is better than the old cost, the new coefficients are chosen. If the new solution is worse, there is a temperature-dependent probability it will be randomly selected anyway. This allows the algo to sample the problem space widely. As iterations progress, the temperature decreases and the algorithm rejects poor solutions more regularly, theoretically honing in on a global minimum.

Constructors
Constructor and Description
`SimulatedAnealingMinimizer()`

All Methods Static Methods Concrete Methods
Modifier and Type	Method and Description
`static MovAvgModel`	`minimize(MovAvgModel model, EvictingQueue<java.lang.Double> train, double[] test)` Runs the simulated annealing algorithm and produces a model with new coefficients that, theoretically fit the data better and generalizes to future forecasts without overfitting.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Class SimulatedAnealingMinimizer