protocol

regressor_protocol

Protocol for machine learning regressors.

Availability:
logtalk_load(regression_protocols(loader))
Author: Paulo Moura
Version: 1:0:0
Date: 2026-05-01
Compilation flags:
static
Dependencies:
(none)
Remarks:
(none)
Inherited public predicates:
(none)

Public predicates

learn/3

Learns a regressor from the given dataset object using the specified options.

Compilation flags:
static
Template:
learn(Dataset,Regressor,Options)
Mode and number of proofs:
learn(+object_identifier,-compound,+list(compound)) - one

learn/2

Learns a regressor from the given dataset object using default options.

Compilation flags:
static
Template:
learn(Dataset,Regressor)
Mode and number of proofs:
learn(+object_identifier,-compound) - one

predict/3

Predicts the numeric target value for a new instance using the learned regressor. The instance is a list of Attribute-Value pairs.

Compilation flags:
static
Template:
predict(Regressor,Instance,Target)
Mode and number of proofs:
predict(+compound,+list,-number) - one

check_regressor/1

Checks that a learned regressor term is structurally valid for the receiving implementation. Throws an exception when the term is not a valid regressor representation.

Compilation flags:
static
Template:
check_regressor(Regressor)
Mode and number of proofs:
check_regressor(@compound) - one_or_error
Exceptions:
Regressor is a variable:
instantiation_error
Regressor is neither a variable nor a valid regressor:
domain_error(regressor,Regressor)

valid_regressor/1

True when a learned regressor term is structurally valid for the receiving implementation. Succeeds iff check_regressor/1 succeeds without throwing an exception.

Compilation flags:
static
Template:
valid_regressor(Regressor)
Mode and number of proofs:
valid_regressor(@compound) - zero_or_one

diagnostics/2

Returns diagnostics metadata for a learned regressor.

Compilation flags:
static
Template:
diagnostics(Regressor,Diagnostics)
Mode and number of proofs:
diagnostics(+compound,-list(compound)) - one

diagnostic/2

Enumerates individual diagnostics metadata terms for a learned regressor.

Compilation flags:
static
Template:
diagnostic(Regressor,Diagnostic)
Mode and number of proofs:
diagnostic(+compound,?compound) - zero_or_more

regressor_options/2

Returns the effective options stored in a learned regressor diagnostics metadata.

Compilation flags:
static
Template:
regressor_options(Regressor,Options)
Mode and number of proofs:
regressor_options(+compound,-list(compound)) - one

export_to_clauses/4

Converts a regressor into a list of predicate clauses. Functor is the functor for the generated predicate clauses. When exporting a serialized regressor term, a noun such as regressor or model is usually clearer than a verb such as predict.

Compilation flags:
static
Template:
export_to_clauses(Dataset,Regressor,Functor,Clauses)
Mode and number of proofs:
export_to_clauses(+object_identifier,+compound,+callable,-list(clause)) - one

export_to_file/4

Exports a regressor to a file. Functor is the functor for the generated predicate clauses. When exporting a serialized regressor term, a noun such as regressor or model is usually clearer than a verb such as predict.

Compilation flags:
static
Template:
export_to_file(Dataset,Regressor,Functor,File)
Mode and number of proofs:
export_to_file(+object_identifier,+compound,+callable,+atom) - one

Protected predicates

(none)

Private predicates

(none)

Operators

(none)

See also

linear_regression, regression_dataset_protocol