Hello, Kim! Thanks for your question.
We have documentation covering our Time-series partitioning here and here. Best it is described by our set up screen:
But I will try to answer your questions:
1) Holdout (Test is confusing naming) - has the same meaning as in any Data Science project - this is unseen data for the model, so for Time-series it is the latest partition of data.
Validation - data partition that precedes Holdout, (you can see on image 3 green parts for validation)
Training - data that precedes Validation or Holdout to create all the features needed.
2) In the number of backtests you can remove the Holdout
3) Backtests are used to choose the best performing blueprint among trained blueprints. The final model is the blueprint retrained on the whole dataset, so it can tune hyperparameters separately. But it is still possible to set those hyperparameters in advanced options of blueprint yourself.
4) You can do that. But I should warn you that this will have little to no effect on the model training, as validation and training partitions are separated by time and most important data will be presented in validation only. We recommend using validation length for this proposes. So selecting a model by its performance on the most important period of time.
Hope this helps.