CBDA_Top_Ranked: CBDA Top-Ranked selection function for Compressive Big Data...
In CBDA: Compressive Big Data Analytics

This CBDA function has all the features of the *Consolidation()* function but allows to choose a different **top** value (i.e., different from the one specified in the main *CBDA()* function

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CBDA_Top_Ranked(top_new = 500, label = "CBDA_package_test", Kcol_min = 5,
  Kcol_max = 15, Nrow_min = 30, Nrow_max = 50, misValperc = 0,
  M = 3000, workspace_directory = getwd())

`top_new`	The new value for the Top predictions to select out of the M
`label`	This is the label appended to RData workspaces generated within the CBDA calls
`Kcol_min`	Lower bound for the percentage of features-columns sampling (used for the Feature Sampling Range - FSR)
`Kcol_max`	Upper bound for the percentage of features-columns sampling (used for the Feature Sampling Range - FSR)
`Nrow_min`	Lower bound for the percentage of cases-rows sampling (used for the Case Sampling Range - CSR)
`Nrow_max`	Upper bound for the percentage of cases-rows sampling (used for the Case Sampling Range - CSR)
`misValperc`	Percentage of missing values to introduce in BigData (used just for testing, to mimic real cases).
`M`	Number of the BigData subsets on which perform Knockoff Filtering and SuperLearner feature mining
`workspace_directory`	Directory where the results and workspaces are saved