{-# LANGUAGE DeriveGeneric #-} {-# LANGUAGE DuplicateRecordFields #-} {-# LANGUAGE NamedFieldPuns #-} {-# LANGUAGE OverloadedStrings #-} {-# LANGUAGE RecordWildCards #-} {-# LANGUAGE StrictData #-} {-# LANGUAGE NoImplicitPrelude #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} {-# OPTIONS_GHC -fno-warn-unused-matches #-} -- Derived from AWS service descriptions, licensed under Apache 2.0. -- | -- Module : Amazonka.Glue.Types.FindMatchesParameters -- Copyright : (c) 2013-2023 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated -- Portability : non-portable (GHC extensions) module Amazonka.Glue.Types.FindMatchesParameters where import qualified Amazonka.Core as Core import qualified Amazonka.Core.Lens.Internal as Lens import qualified Amazonka.Data as Data import qualified Amazonka.Prelude as Prelude -- | The parameters to configure the find matches transform. -- -- /See:/ 'newFindMatchesParameters' smart constructor. data FindMatchesParameters = FindMatchesParameters' { -- | The value that is selected when tuning your transform for a balance -- between accuracy and cost. A value of 0.5 means that the system balances -- accuracy and cost concerns. A value of 1.0 means a bias purely for -- accuracy, which typically results in a higher cost, sometimes -- substantially higher. A value of 0.0 means a bias purely for cost, which -- results in a less accurate @FindMatches@ transform, sometimes with -- unacceptable accuracy. -- -- Accuracy measures how well the transform finds true positives and true -- negatives. Increasing accuracy requires more machine resources and cost. -- But it also results in increased recall. -- -- Cost measures how many compute resources, and thus money, are consumed -- to run the transform. accuracyCostTradeoff :: Prelude.Maybe Prelude.Double, -- | The value to switch on or off to force the output to match the provided -- labels from users. If the value is @True@, the @find matches@ transform -- forces the output to match the provided labels. The results override the -- normal conflation results. If the value is @False@, the @find matches@ -- transform does not ensure all the labels provided are respected, and the -- results rely on the trained model. -- -- Note that setting this value to true may increase the conflation -- execution time. enforceProvidedLabels :: Prelude.Maybe Prelude.Bool, -- | The value selected when tuning your transform for a balance between -- precision and recall. A value of 0.5 means no preference; a value of 1.0 -- means a bias purely for precision, and a value of 0.0 means a bias for -- recall. Because this is a tradeoff, choosing values close to 1.0 means -- very low recall, and choosing values close to 0.0 results in very low -- precision. -- -- The precision metric indicates how often your model is correct when it -- predicts a match. -- -- The recall metric indicates that for an actual match, how often your -- model predicts the match. precisionRecallTradeoff :: Prelude.Maybe Prelude.Double, -- | The name of a column that uniquely identifies rows in the source table. -- Used to help identify matching records. primaryKeyColumnName :: Prelude.Maybe Prelude.Text } deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic) -- | -- Create a value of 'FindMatchesParameters' with all optional fields omitted. -- -- Use or to modify other optional fields. -- -- The following record fields are available, with the corresponding lenses provided -- for backwards compatibility: -- -- 'accuracyCostTradeoff', 'findMatchesParameters_accuracyCostTradeoff' - The value that is selected when tuning your transform for a balance -- between accuracy and cost. A value of 0.5 means that the system balances -- accuracy and cost concerns. A value of 1.0 means a bias purely for -- accuracy, which typically results in a higher cost, sometimes -- substantially higher. A value of 0.0 means a bias purely for cost, which -- results in a less accurate @FindMatches@ transform, sometimes with -- unacceptable accuracy. -- -- Accuracy measures how well the transform finds true positives and true -- negatives. Increasing accuracy requires more machine resources and cost. -- But it also results in increased recall. -- -- Cost measures how many compute resources, and thus money, are consumed -- to run the transform. -- -- 'enforceProvidedLabels', 'findMatchesParameters_enforceProvidedLabels' - The value to switch on or off to force the output to match the provided -- labels from users. If the value is @True@, the @find matches@ transform -- forces the output to match the provided labels. The results override the -- normal conflation results. If the value is @False@, the @find matches@ -- transform does not ensure all the labels provided are respected, and the -- results rely on the trained model. -- -- Note that setting this value to true may increase the conflation -- execution time. -- -- 'precisionRecallTradeoff', 'findMatchesParameters_precisionRecallTradeoff' - The value selected when tuning your transform for a balance between -- precision and recall. A value of 0.5 means no preference; a value of 1.0 -- means a bias purely for precision, and a value of 0.0 means a bias for -- recall. Because this is a tradeoff, choosing values close to 1.0 means -- very low recall, and choosing values close to 0.0 results in very low -- precision. -- -- The precision metric indicates how often your model is correct when it -- predicts a match. -- -- The recall metric indicates that for an actual match, how often your -- model predicts the match. -- -- 'primaryKeyColumnName', 'findMatchesParameters_primaryKeyColumnName' - The name of a column that uniquely identifies rows in the source table. -- Used to help identify matching records. newFindMatchesParameters :: FindMatchesParameters newFindMatchesParameters = FindMatchesParameters' { accuracyCostTradeoff = Prelude.Nothing, enforceProvidedLabels = Prelude.Nothing, precisionRecallTradeoff = Prelude.Nothing, primaryKeyColumnName = Prelude.Nothing } -- | The value that is selected when tuning your transform for a balance -- between accuracy and cost. A value of 0.5 means that the system balances -- accuracy and cost concerns. A value of 1.0 means a bias purely for -- accuracy, which typically results in a higher cost, sometimes -- substantially higher. A value of 0.0 means a bias purely for cost, which -- results in a less accurate @FindMatches@ transform, sometimes with -- unacceptable accuracy. -- -- Accuracy measures how well the transform finds true positives and true -- negatives. Increasing accuracy requires more machine resources and cost. -- But it also results in increased recall. -- -- Cost measures how many compute resources, and thus money, are consumed -- to run the transform. findMatchesParameters_accuracyCostTradeoff :: Lens.Lens' FindMatchesParameters (Prelude.Maybe Prelude.Double) findMatchesParameters_accuracyCostTradeoff = Lens.lens (\FindMatchesParameters' {accuracyCostTradeoff} -> accuracyCostTradeoff) (\s@FindMatchesParameters' {} a -> s {accuracyCostTradeoff = a} :: FindMatchesParameters) -- | The value to switch on or off to force the output to match the provided -- labels from users. If the value is @True@, the @find matches@ transform -- forces the output to match the provided labels. The results override the -- normal conflation results. If the value is @False@, the @find matches@ -- transform does not ensure all the labels provided are respected, and the -- results rely on the trained model. -- -- Note that setting this value to true may increase the conflation -- execution time. findMatchesParameters_enforceProvidedLabels :: Lens.Lens' FindMatchesParameters (Prelude.Maybe Prelude.Bool) findMatchesParameters_enforceProvidedLabels = Lens.lens (\FindMatchesParameters' {enforceProvidedLabels} -> enforceProvidedLabels) (\s@FindMatchesParameters' {} a -> s {enforceProvidedLabels = a} :: FindMatchesParameters) -- | The value selected when tuning your transform for a balance between -- precision and recall. A value of 0.5 means no preference; a value of 1.0 -- means a bias purely for precision, and a value of 0.0 means a bias for -- recall. Because this is a tradeoff, choosing values close to 1.0 means -- very low recall, and choosing values close to 0.0 results in very low -- precision. -- -- The precision metric indicates how often your model is correct when it -- predicts a match. -- -- The recall metric indicates that for an actual match, how often your -- model predicts the match. findMatchesParameters_precisionRecallTradeoff :: Lens.Lens' FindMatchesParameters (Prelude.Maybe Prelude.Double) findMatchesParameters_precisionRecallTradeoff = Lens.lens (\FindMatchesParameters' {precisionRecallTradeoff} -> precisionRecallTradeoff) (\s@FindMatchesParameters' {} a -> s {precisionRecallTradeoff = a} :: FindMatchesParameters) -- | The name of a column that uniquely identifies rows in the source table. -- Used to help identify matching records. findMatchesParameters_primaryKeyColumnName :: Lens.Lens' FindMatchesParameters (Prelude.Maybe Prelude.Text) findMatchesParameters_primaryKeyColumnName = Lens.lens (\FindMatchesParameters' {primaryKeyColumnName} -> primaryKeyColumnName) (\s@FindMatchesParameters' {} a -> s {primaryKeyColumnName = a} :: FindMatchesParameters) instance Data.FromJSON FindMatchesParameters where parseJSON = Data.withObject "FindMatchesParameters" ( \x -> FindMatchesParameters' Prelude.<$> (x Data..:? "AccuracyCostTradeoff") Prelude.<*> (x Data..:? "EnforceProvidedLabels") Prelude.<*> (x Data..:? "PrecisionRecallTradeoff") Prelude.<*> (x Data..:? "PrimaryKeyColumnName") ) instance Prelude.Hashable FindMatchesParameters where hashWithSalt _salt FindMatchesParameters' {..} = _salt `Prelude.hashWithSalt` accuracyCostTradeoff `Prelude.hashWithSalt` enforceProvidedLabels `Prelude.hashWithSalt` precisionRecallTradeoff `Prelude.hashWithSalt` primaryKeyColumnName instance Prelude.NFData FindMatchesParameters where rnf FindMatchesParameters' {..} = Prelude.rnf accuracyCostTradeoff `Prelude.seq` Prelude.rnf enforceProvidedLabels `Prelude.seq` Prelude.rnf precisionRecallTradeoff `Prelude.seq` Prelude.rnf primaryKeyColumnName instance Data.ToJSON FindMatchesParameters where toJSON FindMatchesParameters' {..} = Data.object ( Prelude.catMaybes [ ("AccuracyCostTradeoff" Data..=) Prelude.<$> accuracyCostTradeoff, ("EnforceProvidedLabels" Data..=) Prelude.<$> enforceProvidedLabels, ("PrecisionRecallTradeoff" Data..=) Prelude.<$> precisionRecallTradeoff, ("PrimaryKeyColumnName" Data..=) Prelude.<$> primaryKeyColumnName ] )