Coverage (Deep Java Library 0.24.0 API specification)

java.lang.Object
- ai.djl.training.evaluator.Evaluator
- - ai.djl.training.evaluator.AbstractAccuracy
  - - ai.djl.training.evaluator.Coverage

```
public class Coverage
extends AbstractAccuracy
```
Coverage for a Regression problem: it measures the percent of predictions greater than the actual target, to determine whether the predictor is over-forecasting or under-forecasting. e.g. 0.50 if we predict near the median of the distribution.
```
  def coverage(target, forecast):
     return (np.mean((target < forecast)))
 
```
...

Field Summary
- Fields inherited from class ai.djl.training.evaluator.AbstractAccuracy
  axis, correctInstances
- Fields inherited from class ai.djl.training.evaluator.Evaluator
  totalInstances

Constructor Summary

Constructors
Constructor	Description
`Coverage()`	Creates an evaluator that measures the percent of predictions greater than the actual target.
`Coverage(java.lang.String name, int axis)`	Creates an evaluator that measures the percent of predictions greater than the actual target.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`protected ai.djl.util.Pair<java.lang.Long,NDArray>`	`accuracyHelper(NDList labels, NDList predictions)`	A helper for classes extending `AbstractAccuracy`.

Methods inherited from class ai.djl.training.evaluator.AbstractAccuracy
addAccumulator, evaluate, getAccumulator, resetAccumulator, updateAccumulator

Methods inherited from class ai.djl.training.evaluator.Evaluator
checkLabelShapes, checkLabelShapes, getName

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

- Constructor Detail
  - Coverage
```
public Coverage()
```
    Creates an evaluator that measures the percent of predictions greater than the actual target.
  - Coverage
```
public Coverage(java.lang.String name,
                int axis)
```
    Creates an evaluator that measures the percent of predictions greater than the actual target.
    
    Parameters:
    
    name - the name of the evaluator, default is "Coverage"
    
    axis - the axis along which to count the correct prediction, default is 1
- Method Detail
  - accuracyHelper
```
protected ai.djl.util.Pair<java.lang.Long,NDArray> accuracyHelper(NDList labels,
                                                                        NDList predictions)
```
    A helper for classes extending AbstractAccuracy.
    
    Specified by:
    
    accuracyHelper in class AbstractAccuracy
    
    Parameters:
    
    labels - the labels to get accuracy for
    
    predictions - the predictions to get accuracy for
    
    Returns:
    
    a pair(number of total values, ndarray int of correct values)