OmicSelector_best_signature_proposals — OmicSelector_best_signature

Propose the best signture based on benchamrk methods. This function calculated the `metaindex` value which is the harmonic mean of accuracy on train, test and validation dataset. In the next step, it sorts the miRNA sets based on `metaIndex1` score. The first row in resulting data frame is the winner miRNA set.

Usage

OmicSelector_best_signature_proposals(
  benchmark_csv = "benchmark1578929876.21765.csv",
  without_train = F
)

Arguments

benchmark_csv: Path to benchmark csv.
without_train: One can argue, that accuracy on training dataset should not be used in calculation of metaIndex. By setting this to TRUE, you can calculate it without train dataset.

Value

The benchmark sorted by metaIndex. First row is the best performing miRNA set.