module NMap : Stats.Finbij.S with type elt = Free_variable.ttype problem = | Non_degenerate of {lines : constrnt list;input : Maths.matrix;output : Maths.matrix;nmap : NMap.t;}| Degenerate of {predicted : Maths.matrix;measured : Maths.matrix;}type scores = {r2_score : float option;rmse_score : float;tvalues : (Free_variable.t * float) list;}val scores_encoding : scores Tezos_base.TzPervasives.Data_encoding.tval pp_scores : Stdlib.Format.formatter -> scores -> unitval scores_to_csv_column : (string * Namespace.t) -> scores -> Csv.csvtype solution = {mapping : (Free_variable.t * float) list;weights : Maths.matrix;intercept_lift : float;The diff required to overestimate all measurements by the predictions. This diff should be applied to the intercept parameter when this solution is for the allocation costs.
*)scores : scores;}val pp_error_statistics : Stdlib.Format.formatter -> error_statistics -> unitval compute_error_statistics :
predicted:Maths.matrix ->
measured:Maths.matrix ->
error_statisticsCompute prediction error
val make_problem :
data:'workload Measure.workload_data ->
model:'workload Model.t ->
overrides:(Free_variable.t -> float option) ->
problemmake_problem ~data ~model ~overrides makes a benchmark problem for a solver from the workload data and the model model. overrides specify the variables whose values are already known.
solve_problem problem solver solves problem using solver.
val mapping_to_csv :
(Free_variable.t * float) Tezos_base.TzPervasives.trace ->
Csv.csv