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Module Gpr_interfaces.Sigs.Eval.Stats

module Stats: sig .. end
Statistics derived from trained models
type t = {
   n_samples : int; (*
Number of samples used for training
*)
   target_variance : float; (*
Variance of targets
*)
   sse : float; (*
Sum of squared errors
*)
   mse : float; (*
Mean sum of squared errors
*)
   rmse : float; (*
Root mean sum of squared errors
*)
   smse : float; (*
Standardized mean squared error
*)
   msll : float; (*
Mean standardized log loss
*)
   mad : float; (*
Mean absolute deviation
*)
   maxad : float; (*
Maximum absolute deviation
*)
}
Type of full statistics
val calc_n_samples : Gpr_interfaces.Sigs.Eval.Trained.t -> int
calc_n_samples trained
Returns number of samples used for training trained.
val calc_target_variance : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_target_variance trained
Returns variance of targets used for training trained.
val calc_sse : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_sse trained
Returns the sum of squared errors of the trained model.
val calc_mse : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_mse trained
Returns the mean sum of squared errors of the trained model.
val calc_rmse : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_sse trained
Returns the root of the mean sum of squared errors of the trained model.
val calc_smse : Gpr_interfaces.Sigs.Eval.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 : Gpr_interfaces.Sigs.Eval.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 : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_mad trained
Returns the mean absolute deviation of the trained model.
val calc_maxad : Gpr_interfaces.Sigs.Eval.Trained.t -> float
calc_mad trained
Returns the maximum absolute deviation of the trained model.
val calc : Gpr_interfaces.Sigs.Eval.Trained.t -> t
calc trained
Returns the full set of statistics associated with the trained model.