[Q] Allow error metrics to compare models without anomaly score?

[breznak]

• on a "strategic" level
  • can we include metrics to compare models (additionally) by sth else than anomaly score, comapre by the metric?
• implementation:
  • I'd like to add MSE, R2 metrics
  • (opt) extend API to enforce algorithms to give also prediction (appart from anomalyScore), so we can compute these metrics for all algs? E(current, predicted) -> Real

Justification:

• for some (most?) time-series algorithms provide prediction for T+1, but computing anomaly is sometimes impossible/difficult. See #347
• papers more typically provide these error scores for timeseries than anomaly metric. Therefore this repo can serve easily as a benchmark/experimentation with different algorithms & datasets.
• interesting hypothesis: is anomaly score metric the ideal metric for time-series?
• relatively simple change would allow new comparisons & functionality