functor (Spec : Interfaces.Specs.Eval) ->
sig
module type Sig =
sig
module Spec :
sig
module Kernel :
sig
type t = Spec.Kernel.t
type params = Spec.Kernel.params
val create : params -> t
val get_params : t -> params
end
module Inducing :
sig
type t = Spec.Inducing.t
val get_n_points : t -> int
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
end
module Input :
sig
type t = Spec.Input.t
val eval : Kernel.t -> t -> Inducing.t -> Lacaml.D.vec
val weighted_eval :
Kernel.t -> t -> Inducing.t -> coeffs:Lacaml.D.vec -> float
val eval_one : Kernel.t -> t -> float
end
module Inputs :
sig
type t = Spec.Inputs.t
val create : Input.t array -> t
val get_n_points : t -> int
val choose_subset : t -> Gpr_utils.Int_vec.t -> t
val create_inducing : Kernel.t -> t -> Inducing.t
val create_default_kernel_params :
t -> n_inducing:int -> Kernel.params
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
val calc_diag : Kernel.t -> t -> Lacaml.D.vec
val calc_cross :
Kernel.t -> inputs:t -> inducing:Inducing.t -> Lacaml.D.mat
val weighted_eval :
Kernel.t ->
inputs:t ->
inducing:Inducing.t -> coeffs:Lacaml.D.vec -> Lacaml.D.vec
end
end
module Inducing :
sig
type t
val choose_n_first_inputs :
Spec.Kernel.t ->
Spec.Inputs.t -> n_inducing:int -> Spec.Inducing.t
val choose_n_random_inputs :
?rnd_state:Core.Std.Random.State.t ->
Spec.Kernel.t ->
Spec.Inputs.t -> n_inducing:int -> Spec.Inducing.t
val calc : Spec.Kernel.t -> Spec.Inducing.t -> t
val get_points : t -> Spec.Inducing.t
end
module Input :
sig type t val calc : Inducing.t -> Spec.Input.t -> t end
module Inputs :
sig
type t
val create_default_kernel :
Spec.Inputs.t -> n_inducing:int -> Spec.Kernel.t
val calc : Spec.Inputs.t -> Inducing.t -> t
val get_points : t -> Spec.Inputs.t
end
module Model :
sig
type t
type co_variance_coeffs
val calc : Inputs.t -> sigma2:float -> t
val update_sigma2 : t -> float -> t
val calc_log_evidence : t -> float
val calc_co_variance_coeffs : t -> co_variance_coeffs
val get_kernel : t -> Spec.Kernel.t
val get_sigma2 : t -> float
val get_inputs : t -> Inputs.t
val get_inducing : t -> Inducing.t
end
module Trained :
sig
type t
val calc : Model.t -> targets:Lacaml.D.vec -> t
val calc_mean_coeffs : t -> Lacaml.D.vec
val calc_log_evidence : t -> float
val get_model : t -> Model.t
val get_targets : t -> Lacaml.D.vec
end
module Stats :
sig
type t = {
n_samples : int;
target_variance : float;
sse : float;
mse : float;
rmse : float;
smse : float;
msll : float;
mad : float;
maxad : float;
}
val calc_n_samples : Trained.t -> int
val calc_target_variance : Trained.t -> float
val calc_sse : Trained.t -> float
val calc_mse : Trained.t -> float
val calc_rmse : Trained.t -> float
val calc_smse : Trained.t -> float
val calc_msll : Trained.t -> float
val calc_mad : Trained.t -> float
val calc_maxad : Trained.t -> float
val calc : Trained.t -> t
end
module Mean_predictor :
sig
type t
val calc : Spec.Inducing.t -> coeffs:Lacaml.D.vec -> t
val calc_trained : Trained.t -> t
val get_inducing : t -> Spec.Inducing.t
val get_coeffs : t -> Lacaml.D.vec
end
module Mean :
sig
type t
val calc : Mean_predictor.t -> Input.t -> t
val get : t -> float
end
module Means :
sig
type t
val calc : Mean_predictor.t -> Inputs.t -> t
val get : t -> Lacaml.D.vec
end
module Co_variance_predictor :
sig
type t
val calc :
Spec.Kernel.t ->
Spec.Inducing.t -> Model.co_variance_coeffs -> t
val calc_model : Model.t -> t
end
module Variance :
sig
type t
val calc :
Co_variance_predictor.t -> sigma2:float -> Input.t -> t
val get : ?predictive:bool -> t -> float
end
module Variances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.vec
end
module Covariances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.mat
val get_variances : t -> Variances.t
end
module Sampler :
sig
type t
val calc : ?predictive:bool -> Mean.t -> Variance.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> float
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.vec
end
module Cov_sampler :
sig
type t
val calc : ?predictive:bool -> Means.t -> Covariances.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> Lacaml.D.vec
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.mat
end
end
module FITC : Sig
module FIC :
sig
module Spec :
sig
module Kernel :
sig
type t = Spec.Kernel.t
type params = Spec.Kernel.params
val create : params -> t
val get_params : t -> params
end
module Inducing :
sig
type t = Spec.Inducing.t
val get_n_points : t -> int
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
end
module Input :
sig
type t = Spec.Input.t
val eval : Kernel.t -> t -> Inducing.t -> Lacaml.D.vec
val weighted_eval :
Kernel.t -> t -> Inducing.t -> coeffs:Lacaml.D.vec -> float
val eval_one : Kernel.t -> t -> float
end
module Inputs :
sig
type t = Spec.Inputs.t
val create : Input.t array -> t
val get_n_points : t -> int
val choose_subset : t -> Gpr_utils.Int_vec.t -> t
val create_inducing : Kernel.t -> t -> Inducing.t
val create_default_kernel_params :
t -> n_inducing:int -> Kernel.params
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
val calc_diag : Kernel.t -> t -> Lacaml.D.vec
val calc_cross :
Kernel.t -> inputs:t -> inducing:Inducing.t -> Lacaml.D.mat
val weighted_eval :
Kernel.t ->
inputs:t ->
inducing:Inducing.t -> coeffs:Lacaml.D.vec -> Lacaml.D.vec
end
end
module Inducing :
sig
type t = FITC.Inducing.t
val choose_n_first_inputs :
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val choose_n_random_inputs :
?rnd_state:Core.Std.Random.State.t ->
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val calc : FITC.Spec.Kernel.t -> FITC.Spec.Inducing.t -> t
val get_points : t -> FITC.Spec.Inducing.t
end
module Input :
sig
type t = FITC.Input.t
val calc : FITC.Inducing.t -> FITC.Spec.Input.t -> t
end
module Inputs :
sig
type t = FITC.Inputs.t
val create_default_kernel :
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Kernel.t
val calc : FITC.Spec.Inputs.t -> FITC.Inducing.t -> t
val get_points : t -> FITC.Spec.Inputs.t
end
module Model :
sig
type t = FITC.Model.t
type co_variance_coeffs = FITC.Model.co_variance_coeffs
val calc : FITC.Inputs.t -> sigma2:float -> t
val update_sigma2 : t -> float -> t
val calc_log_evidence : t -> float
val calc_co_variance_coeffs : t -> co_variance_coeffs
val get_kernel : t -> FITC.Spec.Kernel.t
val get_sigma2 : t -> float
val get_inputs : t -> FITC.Inputs.t
val get_inducing : t -> FITC.Inducing.t
end
module Trained :
sig
type t = FITC.Trained.t
val calc : FITC.Model.t -> targets:Lacaml.D.vec -> t
val calc_mean_coeffs : t -> Lacaml.D.vec
val calc_log_evidence : t -> float
val get_model : t -> FITC.Model.t
val get_targets : t -> Lacaml.D.vec
end
module Stats :
sig
type t = {
n_samples : int;
target_variance : float;
sse : float;
mse : float;
rmse : float;
smse : float;
msll : float;
mad : float;
maxad : float;
}
val calc_n_samples : Trained.t -> int
val calc_target_variance : Trained.t -> float
val calc_sse : Trained.t -> float
val calc_mse : Trained.t -> float
val calc_rmse : Trained.t -> float
val calc_smse : Trained.t -> float
val calc_msll : Trained.t -> float
val calc_mad : Trained.t -> float
val calc_maxad : Trained.t -> float
val calc : Trained.t -> t
end
module Mean_predictor :
sig
type t = FITC.Mean_predictor.t
val calc : FITC.Spec.Inducing.t -> coeffs:Lacaml.D.vec -> t
val calc_trained : FITC.Trained.t -> t
val get_inducing : t -> FITC.Spec.Inducing.t
val get_coeffs : t -> Lacaml.D.vec
end
module Mean :
sig
type t = FITC.Mean.t
val calc : FITC.Mean_predictor.t -> FITC.Input.t -> t
val get : t -> float
end
module Means :
sig
type t = FITC.Means.t
val calc : FITC.Mean_predictor.t -> FITC.Inputs.t -> t
val get : t -> Lacaml.D.vec
end
module Co_variance_predictor :
sig
type t = FITC.Co_variance_predictor.t
val calc :
FITC.Spec.Kernel.t ->
FITC.Spec.Inducing.t -> FITC.Model.co_variance_coeffs -> t
val calc_model : FITC.Model.t -> t
end
module Variance :
sig
type t = FITC.Variance.t
val calc :
FITC.Co_variance_predictor.t ->
sigma2:float -> FITC.Input.t -> t
val get : ?predictive:bool -> t -> float
end
module Variances :
sig
type t = FITC.Variances.t
val calc_model_inputs : FITC.Model.t -> t
val calc :
FITC.Co_variance_predictor.t ->
sigma2:float -> FITC.Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.vec
end
module Covariances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.mat
val get_variances : t -> Variances.t
end
module Sampler :
sig
type t = FITC.Sampler.t
val calc :
?predictive:bool -> FITC.Mean.t -> FITC.Variance.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> float
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.vec
end
module Cov_sampler :
sig
type t
val calc : ?predictive:bool -> Means.t -> Covariances.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> Lacaml.D.vec
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.mat
end
end
module Variational_FITC :
sig
module Spec :
sig
module Kernel :
sig
type t = Spec.Kernel.t
type params = Spec.Kernel.params
val create : params -> t
val get_params : t -> params
end
module Inducing :
sig
type t = Spec.Inducing.t
val get_n_points : t -> int
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
end
module Input :
sig
type t = Spec.Input.t
val eval : Kernel.t -> t -> Inducing.t -> Lacaml.D.vec
val weighted_eval :
Kernel.t -> t -> Inducing.t -> coeffs:Lacaml.D.vec -> float
val eval_one : Kernel.t -> t -> float
end
module Inputs :
sig
type t = Spec.Inputs.t
val create : Input.t array -> t
val get_n_points : t -> int
val choose_subset : t -> Gpr_utils.Int_vec.t -> t
val create_inducing : Kernel.t -> t -> Inducing.t
val create_default_kernel_params :
t -> n_inducing:int -> Kernel.params
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
val calc_diag : Kernel.t -> t -> Lacaml.D.vec
val calc_cross :
Kernel.t -> inputs:t -> inducing:Inducing.t -> Lacaml.D.mat
val weighted_eval :
Kernel.t ->
inputs:t ->
inducing:Inducing.t -> coeffs:Lacaml.D.vec -> Lacaml.D.vec
end
end
module Inducing :
sig
type t = FITC.Inducing.t
val choose_n_first_inputs :
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val choose_n_random_inputs :
?rnd_state:Core.Std.Random.State.t ->
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val calc : FITC.Spec.Kernel.t -> FITC.Spec.Inducing.t -> t
val get_points : t -> FITC.Spec.Inducing.t
end
module Input :
sig
type t = FITC.Input.t
val calc : FITC.Inducing.t -> FITC.Spec.Input.t -> t
end
module Inputs :
sig
type t = FITC.Inputs.t
val create_default_kernel :
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Kernel.t
val calc : FITC.Spec.Inputs.t -> FITC.Inducing.t -> t
val get_points : t -> FITC.Spec.Inputs.t
end
module Model :
sig
type t
type co_variance_coeffs
val calc : Inputs.t -> sigma2:float -> t
val update_sigma2 : t -> float -> t
val calc_log_evidence : t -> float
val calc_co_variance_coeffs : t -> co_variance_coeffs
val get_kernel : t -> Spec.Kernel.t
val get_sigma2 : t -> float
val get_inputs : t -> Inputs.t
val get_inducing : t -> Inducing.t
end
module Trained :
sig
type t
val calc : Model.t -> targets:Lacaml.D.vec -> t
val calc_mean_coeffs : t -> Lacaml.D.vec
val calc_log_evidence : t -> float
val get_model : t -> Model.t
val get_targets : t -> Lacaml.D.vec
end
module Stats :
sig
type t = {
n_samples : int;
target_variance : float;
sse : float;
mse : float;
rmse : float;
smse : float;
msll : float;
mad : float;
maxad : float;
}
val calc_n_samples : Trained.t -> int
val calc_target_variance : Trained.t -> float
val calc_sse : Trained.t -> float
val calc_mse : Trained.t -> float
val calc_rmse : Trained.t -> float
val calc_smse : Trained.t -> float
val calc_msll : Trained.t -> float
val calc_mad : Trained.t -> float
val calc_maxad : Trained.t -> float
val calc : Trained.t -> t
end
module Mean_predictor :
sig
type t
val calc : Spec.Inducing.t -> coeffs:Lacaml.D.vec -> t
val calc_trained : Trained.t -> t
val get_inducing : t -> Spec.Inducing.t
val get_coeffs : t -> Lacaml.D.vec
end
module Mean :
sig
type t
val calc : Mean_predictor.t -> Input.t -> t
val get : t -> float
end
module Means :
sig
type t
val calc : Mean_predictor.t -> Inputs.t -> t
val get : t -> Lacaml.D.vec
end
module Co_variance_predictor :
sig
type t
val calc :
Spec.Kernel.t ->
Spec.Inducing.t -> Model.co_variance_coeffs -> t
val calc_model : Model.t -> t
end
module Variance :
sig
type t
val calc :
Co_variance_predictor.t -> sigma2:float -> Input.t -> t
val get : ?predictive:bool -> t -> float
end
module Variances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.vec
end
module Covariances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.mat
val get_variances : t -> Variances.t
end
module Sampler :
sig
type t
val calc : ?predictive:bool -> Mean.t -> Variance.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> float
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.vec
end
module Cov_sampler :
sig
type t
val calc : ?predictive:bool -> Means.t -> Covariances.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> Lacaml.D.vec
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.mat
end
end
module Variational_FIC :
sig
module Spec :
sig
module Kernel :
sig
type t = Spec.Kernel.t
type params = Spec.Kernel.params
val create : params -> t
val get_params : t -> params
end
module Inducing :
sig
type t = Spec.Inducing.t
val get_n_points : t -> int
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
end
module Input :
sig
type t = Spec.Input.t
val eval : Kernel.t -> t -> Inducing.t -> Lacaml.D.vec
val weighted_eval :
Kernel.t -> t -> Inducing.t -> coeffs:Lacaml.D.vec -> float
val eval_one : Kernel.t -> t -> float
end
module Inputs :
sig
type t = Spec.Inputs.t
val create : Input.t array -> t
val get_n_points : t -> int
val choose_subset : t -> Gpr_utils.Int_vec.t -> t
val create_inducing : Kernel.t -> t -> Inducing.t
val create_default_kernel_params :
t -> n_inducing:int -> Kernel.params
val calc_upper : Kernel.t -> t -> Lacaml.D.mat
val calc_diag : Kernel.t -> t -> Lacaml.D.vec
val calc_cross :
Kernel.t -> inputs:t -> inducing:Inducing.t -> Lacaml.D.mat
val weighted_eval :
Kernel.t ->
inputs:t ->
inducing:Inducing.t -> coeffs:Lacaml.D.vec -> Lacaml.D.vec
end
end
module Inducing :
sig
type t = FITC.Inducing.t
val choose_n_first_inputs :
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val choose_n_random_inputs :
?rnd_state:Core.Std.Random.State.t ->
FITC.Spec.Kernel.t ->
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Inducing.t
val calc : FITC.Spec.Kernel.t -> FITC.Spec.Inducing.t -> t
val get_points : t -> FITC.Spec.Inducing.t
end
module Input :
sig
type t = FITC.Input.t
val calc : FITC.Inducing.t -> FITC.Spec.Input.t -> t
end
module Inputs :
sig
type t = FITC.Inputs.t
val create_default_kernel :
FITC.Spec.Inputs.t -> n_inducing:int -> FITC.Spec.Kernel.t
val calc : FITC.Spec.Inputs.t -> FITC.Inducing.t -> t
val get_points : t -> FITC.Spec.Inputs.t
end
module Model :
sig
type t = Variational_FITC.Model.t
type co_variance_coeffs =
Variational_FITC.Model.co_variance_coeffs
val calc : Variational_FITC.Inputs.t -> sigma2:float -> t
val update_sigma2 : t -> float -> t
val calc_log_evidence : t -> float
val calc_co_variance_coeffs : t -> co_variance_coeffs
val get_kernel : t -> Variational_FITC.Spec.Kernel.t
val get_sigma2 : t -> float
val get_inputs : t -> Variational_FITC.Inputs.t
val get_inducing : t -> Variational_FITC.Inducing.t
end
module Trained :
sig
type t = Variational_FITC.Trained.t
val calc : Variational_FITC.Model.t -> targets:Lacaml.D.vec -> t
val calc_mean_coeffs : t -> Lacaml.D.vec
val calc_log_evidence : t -> float
val get_model : t -> Variational_FITC.Model.t
val get_targets : t -> Lacaml.D.vec
end
module Stats :
sig
type t = {
n_samples : int;
target_variance : float;
sse : float;
mse : float;
rmse : float;
smse : float;
msll : float;
mad : float;
maxad : float;
}
val calc_n_samples : Trained.t -> int
val calc_target_variance : Trained.t -> float
val calc_sse : Trained.t -> float
val calc_mse : Trained.t -> float
val calc_rmse : Trained.t -> float
val calc_smse : Trained.t -> float
val calc_msll : Trained.t -> float
val calc_mad : Trained.t -> float
val calc_maxad : Trained.t -> float
val calc : Trained.t -> t
end
module Mean_predictor :
sig
type t = Variational_FITC.Mean_predictor.t
val calc :
Variational_FITC.Spec.Inducing.t -> coeffs:Lacaml.D.vec -> t
val calc_trained : Variational_FITC.Trained.t -> t
val get_inducing : t -> Variational_FITC.Spec.Inducing.t
val get_coeffs : t -> Lacaml.D.vec
end
module Mean :
sig
type t = Variational_FITC.Mean.t
val calc :
Variational_FITC.Mean_predictor.t ->
Variational_FITC.Input.t -> t
val get : t -> float
end
module Means :
sig
type t = Variational_FITC.Means.t
val calc :
Variational_FITC.Mean_predictor.t ->
Variational_FITC.Inputs.t -> t
val get : t -> Lacaml.D.vec
end
module Co_variance_predictor :
sig
type t = Variational_FITC.Co_variance_predictor.t
val calc :
Variational_FITC.Spec.Kernel.t ->
Variational_FITC.Spec.Inducing.t ->
Variational_FITC.Model.co_variance_coeffs -> t
val calc_model : Variational_FITC.Model.t -> t
end
module Variance :
sig
type t = Variational_FITC.Variance.t
val calc :
Variational_FITC.Co_variance_predictor.t ->
sigma2:float -> Variational_FITC.Input.t -> t
val get : ?predictive:bool -> t -> float
end
module Variances :
sig
type t = Variational_FITC.Variances.t
val calc_model_inputs : Variational_FITC.Model.t -> t
val calc :
Variational_FITC.Co_variance_predictor.t ->
sigma2:float -> Variational_FITC.Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.vec
end
module Covariances :
sig
type t
val calc_model_inputs : Model.t -> t
val calc :
Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t
val get : ?predictive:bool -> t -> Lacaml.D.mat
val get_variances : t -> Variances.t
end
module Sampler :
sig
type t = Variational_FITC.Sampler.t
val calc :
?predictive:bool ->
Variational_FITC.Mean.t -> Variational_FITC.Variance.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> float
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.vec
end
module Cov_sampler :
sig
type t
val calc : ?predictive:bool -> Means.t -> Covariances.t -> t
val sample : ?rng:Gsl.Rng.t -> t -> Lacaml.D.vec
val samples : ?rng:Gsl.Rng.t -> t -> n:int -> Lacaml.D.mat
end
end
end