#[non_exhaustive]pub struct FindMatchesParametersBuilder { /* private fields */ }
Expand description
A builder for FindMatchesParameters
.
Implementations§
Source§impl FindMatchesParametersBuilder
impl FindMatchesParametersBuilder
Sourcepub fn primary_key_column_name(self, input: impl Into<String>) -> Self
pub fn primary_key_column_name(self, input: impl Into<String>) -> Self
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
Sourcepub fn set_primary_key_column_name(self, input: Option<String>) -> Self
pub fn set_primary_key_column_name(self, input: Option<String>) -> Self
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
Sourcepub fn get_primary_key_column_name(&self) -> &Option<String>
pub fn get_primary_key_column_name(&self) -> &Option<String>
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
Sourcepub fn precision_recall_tradeoff(self, input: f64) -> Self
pub fn precision_recall_tradeoff(self, input: f64) -> Self
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.
Sourcepub fn set_precision_recall_tradeoff(self, input: Option<f64>) -> Self
pub fn set_precision_recall_tradeoff(self, input: Option<f64>) -> Self
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.
Sourcepub fn get_precision_recall_tradeoff(&self) -> &Option<f64>
pub fn get_precision_recall_tradeoff(&self) -> &Option<f64>
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.
Sourcepub fn accuracy_cost_tradeoff(self, input: f64) -> Self
pub fn accuracy_cost_tradeoff(self, input: f64) -> Self
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.
Sourcepub fn set_accuracy_cost_tradeoff(self, input: Option<f64>) -> Self
pub fn set_accuracy_cost_tradeoff(self, input: Option<f64>) -> Self
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.
Sourcepub fn get_accuracy_cost_tradeoff(&self) -> &Option<f64>
pub fn get_accuracy_cost_tradeoff(&self) -> &Option<f64>
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.
Sourcepub fn enforce_provided_labels(self, input: bool) -> Self
pub fn enforce_provided_labels(self, input: bool) -> Self
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.
Sourcepub fn set_enforce_provided_labels(self, input: Option<bool>) -> Self
pub fn set_enforce_provided_labels(self, input: Option<bool>) -> Self
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.
Sourcepub fn get_enforce_provided_labels(&self) -> &Option<bool>
pub fn get_enforce_provided_labels(&self) -> &Option<bool>
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.
Sourcepub fn build(self) -> FindMatchesParameters
pub fn build(self) -> FindMatchesParameters
Consumes the builder and constructs a FindMatchesParameters
.
Trait Implementations§
Source§impl Clone for FindMatchesParametersBuilder
impl Clone for FindMatchesParametersBuilder
Source§fn clone(&self) -> FindMatchesParametersBuilder
fn clone(&self) -> FindMatchesParametersBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Debug for FindMatchesParametersBuilder
impl Debug for FindMatchesParametersBuilder
Source§impl Default for FindMatchesParametersBuilder
impl Default for FindMatchesParametersBuilder
Source§fn default() -> FindMatchesParametersBuilder
fn default() -> FindMatchesParametersBuilder
Source§impl PartialEq for FindMatchesParametersBuilder
impl PartialEq for FindMatchesParametersBuilder
Source§fn eq(&self, other: &FindMatchesParametersBuilder) -> bool
fn eq(&self, other: &FindMatchesParametersBuilder) -> bool
self
and other
values to be equal, and is used by ==
.impl StructuralPartialEq for FindMatchesParametersBuilder
Auto Trait Implementations§
impl Freeze for FindMatchesParametersBuilder
impl RefUnwindSafe for FindMatchesParametersBuilder
impl Send for FindMatchesParametersBuilder
impl Sync for FindMatchesParametersBuilder
impl Unpin for FindMatchesParametersBuilder
impl UnwindSafe for FindMatchesParametersBuilder
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