This is the first release of `scikit-fallback` and it implements rudimentary tools for supporting and evaluating rejections in classification problems:
* `sfkb.estimators.ThresholdFallbackClassifier(CV)` and `RateFallbackClassifier` for (meta-)classification w/ a reject option.
* `skfb.metrics` for Predict-Fallback metrics, confusion matrices, and curves.
* `skfb.core.array` for NDArray-compatible FBNDArray for storing predictions and fallback masks.