fsAmalgam: Reduce Dimensions by Amalgamation
In tpq/exprso: Rapid Deployment of Machine Learning Algorithms

fsAmalgam finds a set of explanatory "amalgams" using the amalgam::amalgam function. This function expects a compositional data set that can be reduced by amalgamation. The resultant "amalgams" are clr- or slr-transformed. The amalgamation rule is saved and deployed automatically by the predict method during test set validation.

1	fsAmalgam(object, top = 0, ...)

`object`	An `ExprsArray` object to undergo feature selection.
`top`	A numeric scalar or character vector. A numeric scalar indicates the number of top features that should undergo feature selection. A character vector indicates specifically which features by name should undergo feature selection. Set `top = 0` to include all features. A numeric vector can also be used to indicate specific features by location, similar to a character vector.
`...`	Arguments passed to the detailed function.