case class AdvancedOptions(blueprintThreshold: Option[Int] = None, responseCap: Option[Double] = None, seed: Option[Int] = None, weights: Option[String] = None, rateTopPctThreshold: Option[Float] = None, offset: Option[String] = None, exposure: Option[String] = None, eventsCount: Option[String] = None, smartDownsampled: Option[Boolean] = None, majorityDownsamplingRate: Option[Double] = None, downsampledMinorityRows: Option[Int] = None, downsampledMajorityRows: Option[Int] = None, accuracyOptimizedMb: Option[Boolean] = None, scaleoutModelingMode: Option[Boolean] = None, defaultMonotonicIncreasingFeaturelistId: Option[String] = None, defaultMonotonicDecreasingFeaturelistId: Option[String] = None, onlyIncludeMonotonicBlueprints: Option[Boolean] = None, blendBestModels: Option[Boolean] = None, minSecondaryValidationModelCount: Option[Int] = None, scoringCodeOnly: Option[Boolean] = None, prepareModelForDeployment: Option[Boolean] = None, allowedPairwiseInteractionGroups: Option[Seq[Seq[String]]] = None) extends Product with Serializable
- blueprintThreshold
an upper bound on running time (in hours), such that models exceeding the bound will be excluded in subsequent autopilot runs
- responseCap
defaults to False, if specified used to cap the maximum response of a model
- seed
defaults to null, the random seed to be used if specified
- weights
the name of the weight column, if specified, otherwise null.
- rateTopPctThreshold
- Optional, the percentage threshold between 0.1 and 50 for specifying the Rate@Top% metric.
- offset
the list of names of the offset columns, if specified, other- wise null.
- exposure
the name of the exposure column, if specified, other- wise null.
- eventsCount
the name of the event count column, if specified, otherwise null.
- smartDownsampled
whether the project uses smart downsampling to throw away excess rows of the majority class. Smart downsampled projects express all sample percents in terms of percent of minority rows (as opposed to percent of all rows).
- majorityDownsamplingRate
the percentage be- tween 0 and 100 of the majority rows that are kept, or null for projects without smart down- sampling
- downsampledMinorityRows
the total number of the minority rows available for modeling, or null for projects without smart downsampling
- downsampledMajorityRows
the total number of the majority rows available for modeling, or null for projects without smart downsampling
- accuracyOptimizedMb
Include additional, longer-running models that will be run by the autopilot and available to run manually
- scaleoutModelingMode
Specifies the behavior of Scaleout models for the project. This is one of disabled, repositoryOnly, autopilot
- defaultMonotonicIncreasingFeaturelistId
null or str, the ID of the featurelist specifying a set of features with a monotonically increasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
- defaultMonotonicDecreasingFeaturelistId
null or str, the ID of the featurelist specifying a set of features with a monotonically decreasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
- onlyIncludeMonotonicBlueprints
boolean (default to False), whether the project only includes blueprints support enforcing monotonic constraints
- blendBestModels
optional, defaults to True. Blend best models during Autopilot run.
- minSecondaryValidationModelCount
optional, defaults to 0. Compute “All backtest” scores (datetime models) or cross validation scores for the specified number of highest ranking models on the Leaderboard, if over the Autopilot default.
- scoringCodeOnly
optional, defaults to False. Keep only models that can be converted to scorable java code during Autopilot run.
- prepareModelForDeployment
optional, defaults to True. Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning “RECOMMENDED FOR DEPLOYMENT” label.
- allowedPairwiseInteractionGroups
(array) –) op- tional. For GAM models - specify groups of columns for which pairwise interactions will be allowed. E.g. if set to “B”, “C”], [“C”, “D” then GAM models will allow interactions between columns AxB, BxC, AxC, CxD. All others (AxD, BxD) will not be considered. If not specified - all possible interactions will be considered by model.
- returns
AdvancedOptions object
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AdvancedOptions(blueprintThreshold: Option[Int] = None, responseCap: Option[Double] = None, seed: Option[Int] = None, weights: Option[String] = None, rateTopPctThreshold: Option[Float] = None, offset: Option[String] = None, exposure: Option[String] = None, eventsCount: Option[String] = None, smartDownsampled: Option[Boolean] = None, majorityDownsamplingRate: Option[Double] = None, downsampledMinorityRows: Option[Int] = None, downsampledMajorityRows: Option[Int] = None, accuracyOptimizedMb: Option[Boolean] = None, scaleoutModelingMode: Option[Boolean] = None, defaultMonotonicIncreasingFeaturelistId: Option[String] = None, defaultMonotonicDecreasingFeaturelistId: Option[String] = None, onlyIncludeMonotonicBlueprints: Option[Boolean] = None, blendBestModels: Option[Boolean] = None, minSecondaryValidationModelCount: Option[Int] = None, scoringCodeOnly: Option[Boolean] = None, prepareModelForDeployment: Option[Boolean] = None, allowedPairwiseInteractionGroups: Option[Seq[Seq[String]]] = None)
The advancedOptions object specifies more settings for a project
The advancedOptions object specifies more settings for a project
- blueprintThreshold
an upper bound on running time (in hours), such that models exceeding the bound will be excluded in subsequent autopilot runs
- responseCap
defaults to False, if specified used to cap the maximum response of a model
- seed
defaults to null, the random seed to be used if specified
- weights
the name of the weight column, if specified, otherwise null.
- rateTopPctThreshold
- Optional, the percentage threshold between 0.1 and 50 for specifying the Rate@Top% metric.
- offset
the list of names of the offset columns, if specified, other- wise null.
- exposure
the name of the exposure column, if specified, other- wise null.
- eventsCount
the name of the event count column, if specified, otherwise null.
- smartDownsampled
whether the project uses smart downsampling to throw away excess rows of the majority class. Smart downsampled projects express all sample percents in terms of percent of minority rows (as opposed to percent of all rows).
- majorityDownsamplingRate
the percentage be- tween 0 and 100 of the majority rows that are kept, or null for projects without smart down- sampling
- downsampledMinorityRows
the total number of the minority rows available for modeling, or null for projects without smart downsampling
- downsampledMajorityRows
the total number of the majority rows available for modeling, or null for projects without smart downsampling
- accuracyOptimizedMb
Include additional, longer-running models that will be run by the autopilot and available to run manually
- scaleoutModelingMode
Specifies the behavior of Scaleout models for the project. This is one of disabled, repositoryOnly, autopilot
- defaultMonotonicIncreasingFeaturelistId
null or str, the ID of the featurelist specifying a set of features with a monotonically increasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
- defaultMonotonicDecreasingFeaturelistId
null or str, the ID of the featurelist specifying a set of features with a monotonically decreasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
- onlyIncludeMonotonicBlueprints
boolean (default to False), whether the project only includes blueprints support enforcing monotonic constraints
- blendBestModels
optional, defaults to True. Blend best models during Autopilot run.
- minSecondaryValidationModelCount
optional, defaults to 0. Compute “All backtest” scores (datetime models) or cross validation scores for the specified number of highest ranking models on the Leaderboard, if over the Autopilot default.
- scoringCodeOnly
optional, defaults to False. Keep only models that can be converted to scorable java code during Autopilot run.
- prepareModelForDeployment
optional, defaults to True. Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning “RECOMMENDED FOR DEPLOYMENT” label.
- allowedPairwiseInteractionGroups
(array) –) op- tional. For GAM models - specify groups of columns for which pairwise interactions will be allowed. E.g. if set to “B”, “C”], [“C”, “D” then GAM models will allow interactions between columns AxB, BxC, AxC, CxD. All others (AxD, BxD) will not be considered. If not specified - all possible interactions will be considered by model.
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- val accuracyOptimizedMb: Option[Boolean]
- val allowedPairwiseInteractionGroups: Option[Seq[Seq[String]]]
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- val blendBestModels: Option[Boolean]
- val blueprintThreshold: Option[Int]
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- val defaultMonotonicDecreasingFeaturelistId: Option[String]
- val defaultMonotonicIncreasingFeaturelistId: Option[String]
- val downsampledMajorityRows: Option[Int]
- val downsampledMinorityRows: Option[Int]
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- val eventsCount: Option[String]
- val exposure: Option[String]
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- val majorityDownsamplingRate: Option[Double]
- val minSecondaryValidationModelCount: Option[Int]
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- val offset: Option[String]
- val onlyIncludeMonotonicBlueprints: Option[Boolean]
- val prepareModelForDeployment: Option[Boolean]
- val rateTopPctThreshold: Option[Float]
- val responseCap: Option[Double]
- val scaleoutModelingMode: Option[Boolean]
- val scoringCodeOnly: Option[Boolean]
- val seed: Option[Int]
- val smartDownsampled: Option[Boolean]
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- val weights: Option[String]
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