src/metrics.bend source

src/metrics.bend on the hub · documented module

import Baseimport ./batch.bend as Batchimport ./numeric.bend as Numerictype Prediction is Data:  Prediction{actual: F32, predicted: F32}type SquaredErrors is Data:  SquaredErrors{n: Nat, total: F32}def singleton(row: Prediction) -> SquaredErrors:  match row:    case Prediction{actual, predicted}:      SquaredErrors{1n, Numeric.squared_error(actual, predicted)}def merge(a: SquaredErrors, b: SquaredErrors) -> SquaredErrors:  match a b:    case SquaredErrors{n1, s1} SquaredErrors{n2, s2}:      SquaredErrors{Nat.add(n1, n2), F32.add(s1, s2)}def checked(ok: Bool, value: F32) -> Maybe<&2, F32>:  match ok:    case False{}:      None{}    case True{}:      Some{value}def finish(stats: SquaredErrors) -> Maybe<&2, F32>:  match stats:    case SquaredErrors{n, total}:      match n:        case 0n:          None{}        case 1n+p:          +value = F32.div(total, F32.from_nat(1n+p))          checked(Numeric.is_finite(value), value)# None means no observations or a non-finite numerical result.def mean_squared_error(rows: Batch.Batch<Prediction>) -> Maybe<&2, F32>:  finish(Batch.fold(~Prediction, ~SquaredErrors, ~singleton, ~merge, SquaredErrors{0n, 0.0}, rows))