[7.x] [ML] calculate feature importance for multi-class results (#1071) #1075
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Feature importance is already calculated for multi-class models. This commit adjusts the output sent to ES so that multi-class importance can be explored.
Feature importance objects are now mapped as follows
(logistic) Regression:
```
{
"feature_name": "feature_0",
"importance": -1.3
}
```
Multi-class [class names are `foo`, `bar`, `baz`]
```
{
“feature_name”: “feature_0”,
“importance”: 2.0, // sum(abs()) of class importances
“foo”: 1.0,
“bar”: 0.5,
“baz”: -0.5
},
```
Java side change: elastic/elasticsearch#53803
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Backports the following commits to 7.x: