package tezos-benchmark

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package tezos-benchmark
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Module Tezos_benchmark.InferenceSource

Sourcetype measure =
  1. | Measure of Maths.vector
Sourcetype constrnt =
  1. | Full of Costlang.affine * measure
Sourcetype problem =
  1. | Non_degenerate of {
    1. lines : constrnt list;
    2. input : Maths.matrix;
    3. output : Maths.matrix;
    4. nmap : NMap.t;
    }
  2. | Degenerate of {
    1. predicted : Maths.matrix;
    2. measured : Maths.matrix;
    }
Sourcetype scores = {
  1. r2_score : float option;
  2. rmse_score : float;
  3. tvalues : (Free_variable.t * float) list;
}
Sourceval pp_scores : Format.formatter -> scores -> unit
Sourceval scores_to_csv_column : (string * Namespace.t) -> scores -> Csv.csv
Sourcetype solution = {
  1. mapping : (Free_variable.t * float) list;
  2. weights : Maths.matrix;
  3. 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.

    *)
  4. scores : scores;
}
Sourcetype solver =
  1. | Ridge of {
    1. alpha : float;
    }
  2. | Lasso of {
    1. alpha : float;
    2. positive : bool;
    }
  3. | NNLS
Sourcetype error_statistics
Sourceval pp_error_statistics : Format.formatter -> error_statistics -> unit
Sourceval compute_error_statistics : predicted:Maths.matrix -> measured:Maths.matrix -> error_statistics

Compute prediction error

Sourceval make_problem : data:'workload Measure.workload_data -> model:'workload Model.t -> overrides:(Free_variable.t -> float option) -> problem

make_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.

Sourceval solve_problem : problem -> solver -> solution

solve_problem problem solver solves problem using solver.

Sourceval problem_to_csv : problem -> Csv.csv
Sourceval solution_to_csv : solution -> Csv.csv option
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