TrainingOptions constructor

TrainingOptions({
  1. String? activationFn,
  2. bool? adjustStepChanges,
  3. bool? approxGlobalFeatureContrib,
  4. bool? autoArima,
  5. String? autoArimaMaxOrder,
  6. String? autoArimaMinOrder,
  7. bool? autoClassWeights,
  8. String? batchSize,
  9. String? boosterType,
  10. double? budgetHours,
  11. bool? calculatePValues,
  12. String? categoryEncodingMethod,
  13. bool? cleanSpikesAndDips,
  14. String? colorSpace,
  15. double? colsampleBylevel,
  16. double? colsampleBynode,
  17. double? colsampleBytree,
  18. String? contributionMetric,
  19. String? dartNormalizeType,
  20. String? dataFrequency,
  21. String? dataSplitColumn,
  22. double? dataSplitEvalFraction,
  23. String? dataSplitMethod,
  24. bool? decomposeTimeSeries,
  25. List<String>? dimensionIdColumns,
  26. String? distanceType,
  27. double? dropout,
  28. bool? earlyStop,
  29. bool? enableGlobalExplain,
  30. String? endpointIdleTtl,
  31. String? feedbackType,
  32. bool? fitIntercept,
  33. double? forecastLimitLowerBound,
  34. double? forecastLimitUpperBound,
  35. List<String>? hiddenUnits,
  36. String? holidayRegion,
  37. List<String>? holidayRegions,
  38. String? horizon,
  39. List<String>? hparamTuningObjectives,
  40. String? huggingFaceModelId,
  41. bool? includeDrift,
  42. double? initialLearnRate,
  43. List<String>? inputLabelColumns,
  44. String? instanceWeightColumn,
  45. String? integratedGradientsNumSteps,
  46. String? isTestColumn,
  47. String? itemColumn,
  48. String? kmeansInitializationColumn,
  49. String? kmeansInitializationMethod,
  50. double? l1RegActivation,
  51. double? l1Regularization,
  52. double? l2Regularization,
  53. Map<String, double>? labelClassWeights,
  54. double? learnRate,
  55. String? learnRateStrategy,
  56. String? lossType,
  57. String? machineType,
  58. String? maxIterations,
  59. String? maxParallelTrials,
  60. String? maxReplicaCount,
  61. String? maxTimeSeriesLength,
  62. String? maxTreeDepth,
  63. double? minAprioriSupport,
  64. double? minRelativeProgress,
  65. String? minReplicaCount,
  66. double? minSplitLoss,
  67. String? minTimeSeriesLength,
  68. String? minTreeChildWeight,
  69. String? modelGardenModelName,
  70. String? modelRegistry,
  71. String? modelUri,
  72. ArimaOrder? nonSeasonalOrder,
  73. String? numClusters,
  74. String? numFactors,
  75. String? numParallelTree,
  76. String? numPrincipalComponents,
  77. String? numTrials,
  78. String? optimizationStrategy,
  79. String? optimizer,
  80. double? pcaExplainedVarianceRatio,
  81. String? pcaSolver,
  82. String? reservationAffinityKey,
  83. String? reservationAffinityType,
  84. List<String>? reservationAffinityValues,
  85. String? sampledShapleyNumPaths,
  86. bool? scaleFeatures,
  87. bool? standardizeFeatures,
  88. double? subsample,
  89. String? tfVersion,
  90. String? timeSeriesDataColumn,
  91. String? timeSeriesIdColumn,
  92. List<String>? timeSeriesIdColumns,
  93. double? timeSeriesLengthFraction,
  94. String? timeSeriesTimestampColumn,
  95. String? treeMethod,
  96. String? trendSmoothingWindowSize,
  97. String? userColumn,
  98. List<String>? vertexAiModelVersionAliases,
  99. double? walsAlpha,
  100. bool? warmStart,
  101. String? xgboostVersion,
})

Implementation

TrainingOptions({
  this.activationFn,
  this.adjustStepChanges,
  this.approxGlobalFeatureContrib,
  this.autoArima,
  this.autoArimaMaxOrder,
  this.autoArimaMinOrder,
  this.autoClassWeights,
  this.batchSize,
  this.boosterType,
  this.budgetHours,
  this.calculatePValues,
  this.categoryEncodingMethod,
  this.cleanSpikesAndDips,
  this.colorSpace,
  this.colsampleBylevel,
  this.colsampleBynode,
  this.colsampleBytree,
  this.contributionMetric,
  this.dartNormalizeType,
  this.dataFrequency,
  this.dataSplitColumn,
  this.dataSplitEvalFraction,
  this.dataSplitMethod,
  this.decomposeTimeSeries,
  this.dimensionIdColumns,
  this.distanceType,
  this.dropout,
  this.earlyStop,
  this.enableGlobalExplain,
  this.endpointIdleTtl,
  this.feedbackType,
  this.fitIntercept,
  this.forecastLimitLowerBound,
  this.forecastLimitUpperBound,
  this.hiddenUnits,
  this.holidayRegion,
  this.holidayRegions,
  this.horizon,
  this.hparamTuningObjectives,
  this.huggingFaceModelId,
  this.includeDrift,
  this.initialLearnRate,
  this.inputLabelColumns,
  this.instanceWeightColumn,
  this.integratedGradientsNumSteps,
  this.isTestColumn,
  this.itemColumn,
  this.kmeansInitializationColumn,
  this.kmeansInitializationMethod,
  this.l1RegActivation,
  this.l1Regularization,
  this.l2Regularization,
  this.labelClassWeights,
  this.learnRate,
  this.learnRateStrategy,
  this.lossType,
  this.machineType,
  this.maxIterations,
  this.maxParallelTrials,
  this.maxReplicaCount,
  this.maxTimeSeriesLength,
  this.maxTreeDepth,
  this.minAprioriSupport,
  this.minRelativeProgress,
  this.minReplicaCount,
  this.minSplitLoss,
  this.minTimeSeriesLength,
  this.minTreeChildWeight,
  this.modelGardenModelName,
  this.modelRegistry,
  this.modelUri,
  this.nonSeasonalOrder,
  this.numClusters,
  this.numFactors,
  this.numParallelTree,
  this.numPrincipalComponents,
  this.numTrials,
  this.optimizationStrategy,
  this.optimizer,
  this.pcaExplainedVarianceRatio,
  this.pcaSolver,
  this.reservationAffinityKey,
  this.reservationAffinityType,
  this.reservationAffinityValues,
  this.sampledShapleyNumPaths,
  this.scaleFeatures,
  this.standardizeFeatures,
  this.subsample,
  this.tfVersion,
  this.timeSeriesDataColumn,
  this.timeSeriesIdColumn,
  this.timeSeriesIdColumns,
  this.timeSeriesLengthFraction,
  this.timeSeriesTimestampColumn,
  this.treeMethod,
  this.trendSmoothingWindowSize,
  this.userColumn,
  this.vertexAiModelVersionAliases,
  this.walsAlpha,
  this.warmStart,
  this.xgboostVersion,
});