package gpr

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Statistics derived from trained models

type t = {
  1. n_samples : int;
    (*

    Number of samples used for training

    *)
  2. target_variance : float;
    (*

    Variance of targets

    *)
  3. sse : float;
    (*

    Sum of squared errors

    *)
  4. mse : float;
    (*

    Mean sum of squared errors

    *)
  5. rmse : float;
    (*

    Root mean sum of squared errors

    *)
  6. smse : float;
    (*

    Standardized mean squared error

    *)
  7. msll : float;
    (*

    Mean standardized log loss

    *)
  8. mad : float;
    (*

    Mean absolute deviation

    *)
  9. maxad : float;
    (*

    Maximum absolute deviation

    *)
}

Type of full statistics

val calc_n_samples : Trained.t -> int

calc_n_samples trained

  • returns

    number of samples used for training trained.

val calc_target_variance : Trained.t -> float

calc_target_variance trained

  • returns

    variance of targets used for training trained.

val calc_sse : Trained.t -> float

calc_sse trained

  • returns

    the sum of squared errors of the trained model.

val calc_mse : Trained.t -> float

calc_mse trained

  • returns

    the mean sum of squared errors of the trained model.

val calc_rmse : Trained.t -> float

calc_sse trained

  • returns

    the root of the mean sum of squared errors of the trained model.

val calc_smse : Trained.t -> float

calc_smse trained

  • returns

    the standardized mean squared error of the trained model. This is equivalent to the mean squared error divided by the target variance.

val calc_msll : Trained.t -> float

calc_msll trained

  • returns

    the mean standardized log loss. This is equivalent to subtracting the log evidence of the trained model from the log evidence of a normal distribution fit to the targets, and dividing the result by the number of samples.

val calc_mad : Trained.t -> float

calc_mad trained

  • returns

    the mean absolute deviation of the trained model.

val calc_maxad : Trained.t -> float

calc_mad trained

  • returns

    the maximum absolute deviation of the trained model.

val calc : Trained.t -> t

calc trained

  • returns

    the full set of statistics associated with the trained model.

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