TrainingOptions.fromJson constructor

TrainingOptions.fromJson(Map json_)

Implementation

TrainingOptions.fromJson(core.Map json_)
    : this(
        activationFn: json_.containsKey('activationFn')
            ? json_['activationFn'] as core.String
            : null,
        adjustStepChanges: json_.containsKey('adjustStepChanges')
            ? json_['adjustStepChanges'] as core.bool
            : null,
        approxGlobalFeatureContrib:
            json_.containsKey('approxGlobalFeatureContrib')
                ? json_['approxGlobalFeatureContrib'] as core.bool
                : null,
        autoArima: json_.containsKey('autoArima')
            ? json_['autoArima'] as core.bool
            : null,
        autoArimaMaxOrder: json_.containsKey('autoArimaMaxOrder')
            ? json_['autoArimaMaxOrder'] as core.String
            : null,
        autoArimaMinOrder: json_.containsKey('autoArimaMinOrder')
            ? json_['autoArimaMinOrder'] as core.String
            : null,
        autoClassWeights: json_.containsKey('autoClassWeights')
            ? json_['autoClassWeights'] as core.bool
            : null,
        batchSize: json_.containsKey('batchSize')
            ? json_['batchSize'] as core.String
            : null,
        boosterType: json_.containsKey('boosterType')
            ? json_['boosterType'] as core.String
            : null,
        budgetHours: json_.containsKey('budgetHours')
            ? (json_['budgetHours'] as core.num).toDouble()
            : null,
        calculatePValues: json_.containsKey('calculatePValues')
            ? json_['calculatePValues'] as core.bool
            : null,
        categoryEncodingMethod: json_.containsKey('categoryEncodingMethod')
            ? json_['categoryEncodingMethod'] as core.String
            : null,
        cleanSpikesAndDips: json_.containsKey('cleanSpikesAndDips')
            ? json_['cleanSpikesAndDips'] as core.bool
            : null,
        colorSpace: json_.containsKey('colorSpace')
            ? json_['colorSpace'] as core.String
            : null,
        colsampleBylevel: json_.containsKey('colsampleBylevel')
            ? (json_['colsampleBylevel'] as core.num).toDouble()
            : null,
        colsampleBynode: json_.containsKey('colsampleBynode')
            ? (json_['colsampleBynode'] as core.num).toDouble()
            : null,
        colsampleBytree: json_.containsKey('colsampleBytree')
            ? (json_['colsampleBytree'] as core.num).toDouble()
            : null,
        dartNormalizeType: json_.containsKey('dartNormalizeType')
            ? json_['dartNormalizeType'] as core.String
            : null,
        dataFrequency: json_.containsKey('dataFrequency')
            ? json_['dataFrequency'] as core.String
            : null,
        dataSplitColumn: json_.containsKey('dataSplitColumn')
            ? json_['dataSplitColumn'] as core.String
            : null,
        dataSplitEvalFraction: json_.containsKey('dataSplitEvalFraction')
            ? (json_['dataSplitEvalFraction'] as core.num).toDouble()
            : null,
        dataSplitMethod: json_.containsKey('dataSplitMethod')
            ? json_['dataSplitMethod'] as core.String
            : null,
        decomposeTimeSeries: json_.containsKey('decomposeTimeSeries')
            ? json_['decomposeTimeSeries'] as core.bool
            : null,
        distanceType: json_.containsKey('distanceType')
            ? json_['distanceType'] as core.String
            : null,
        dropout: json_.containsKey('dropout')
            ? (json_['dropout'] as core.num).toDouble()
            : null,
        earlyStop: json_.containsKey('earlyStop')
            ? json_['earlyStop'] as core.bool
            : null,
        enableGlobalExplain: json_.containsKey('enableGlobalExplain')
            ? json_['enableGlobalExplain'] as core.bool
            : null,
        feedbackType: json_.containsKey('feedbackType')
            ? json_['feedbackType'] as core.String
            : null,
        fitIntercept: json_.containsKey('fitIntercept')
            ? json_['fitIntercept'] as core.bool
            : null,
        hiddenUnits: json_.containsKey('hiddenUnits')
            ? (json_['hiddenUnits'] as core.List)
                .map((value) => value as core.String)
                .toList()
            : null,
        holidayRegion: json_.containsKey('holidayRegion')
            ? json_['holidayRegion'] as core.String
            : null,
        holidayRegions: json_.containsKey('holidayRegions')
            ? (json_['holidayRegions'] as core.List)
                .map((value) => value as core.String)
                .toList()
            : null,
        horizon: json_.containsKey('horizon')
            ? json_['horizon'] as core.String
            : null,
        hparamTuningObjectives: json_.containsKey('hparamTuningObjectives')
            ? (json_['hparamTuningObjectives'] as core.List)
                .map((value) => value as core.String)
                .toList()
            : null,
        includeDrift: json_.containsKey('includeDrift')
            ? json_['includeDrift'] as core.bool
            : null,
        initialLearnRate: json_.containsKey('initialLearnRate')
            ? (json_['initialLearnRate'] as core.num).toDouble()
            : null,
        inputLabelColumns: json_.containsKey('inputLabelColumns')
            ? (json_['inputLabelColumns'] as core.List)
                .map((value) => value as core.String)
                .toList()
            : null,
        instanceWeightColumn: json_.containsKey('instanceWeightColumn')
            ? json_['instanceWeightColumn'] as core.String
            : null,
        integratedGradientsNumSteps:
            json_.containsKey('integratedGradientsNumSteps')
                ? json_['integratedGradientsNumSteps'] as core.String
                : null,
        itemColumn: json_.containsKey('itemColumn')
            ? json_['itemColumn'] as core.String
            : null,
        kmeansInitializationColumn:
            json_.containsKey('kmeansInitializationColumn')
                ? json_['kmeansInitializationColumn'] as core.String
                : null,
        kmeansInitializationMethod:
            json_.containsKey('kmeansInitializationMethod')
                ? json_['kmeansInitializationMethod'] as core.String
                : null,
        l1RegActivation: json_.containsKey('l1RegActivation')
            ? (json_['l1RegActivation'] as core.num).toDouble()
            : null,
        l1Regularization: json_.containsKey('l1Regularization')
            ? (json_['l1Regularization'] as core.num).toDouble()
            : null,
        l2Regularization: json_.containsKey('l2Regularization')
            ? (json_['l2Regularization'] as core.num).toDouble()
            : null,
        labelClassWeights: json_.containsKey('labelClassWeights')
            ? (json_['labelClassWeights']
                    as core.Map<core.String, core.dynamic>)
                .map(
                (key, value) => core.MapEntry(
                  key,
                  (value as core.num).toDouble(),
                ),
              )
            : null,
        learnRate: json_.containsKey('learnRate')
            ? (json_['learnRate'] as core.num).toDouble()
            : null,
        learnRateStrategy: json_.containsKey('learnRateStrategy')
            ? json_['learnRateStrategy'] as core.String
            : null,
        lossType: json_.containsKey('lossType')
            ? json_['lossType'] as core.String
            : null,
        maxIterations: json_.containsKey('maxIterations')
            ? json_['maxIterations'] as core.String
            : null,
        maxParallelTrials: json_.containsKey('maxParallelTrials')
            ? json_['maxParallelTrials'] as core.String
            : null,
        maxTimeSeriesLength: json_.containsKey('maxTimeSeriesLength')
            ? json_['maxTimeSeriesLength'] as core.String
            : null,
        maxTreeDepth: json_.containsKey('maxTreeDepth')
            ? json_['maxTreeDepth'] as core.String
            : null,
        minRelativeProgress: json_.containsKey('minRelativeProgress')
            ? (json_['minRelativeProgress'] as core.num).toDouble()
            : null,
        minSplitLoss: json_.containsKey('minSplitLoss')
            ? (json_['minSplitLoss'] as core.num).toDouble()
            : null,
        minTimeSeriesLength: json_.containsKey('minTimeSeriesLength')
            ? json_['minTimeSeriesLength'] as core.String
            : null,
        minTreeChildWeight: json_.containsKey('minTreeChildWeight')
            ? json_['minTreeChildWeight'] as core.String
            : null,
        modelRegistry: json_.containsKey('modelRegistry')
            ? json_['modelRegistry'] as core.String
            : null,
        modelUri: json_.containsKey('modelUri')
            ? json_['modelUri'] as core.String
            : null,
        nonSeasonalOrder: json_.containsKey('nonSeasonalOrder')
            ? ArimaOrder.fromJson(json_['nonSeasonalOrder']
                as core.Map<core.String, core.dynamic>)
            : null,
        numClusters: json_.containsKey('numClusters')
            ? json_['numClusters'] as core.String
            : null,
        numFactors: json_.containsKey('numFactors')
            ? json_['numFactors'] as core.String
            : null,
        numParallelTree: json_.containsKey('numParallelTree')
            ? json_['numParallelTree'] as core.String
            : null,
        numPrincipalComponents: json_.containsKey('numPrincipalComponents')
            ? json_['numPrincipalComponents'] as core.String
            : null,
        numTrials: json_.containsKey('numTrials')
            ? json_['numTrials'] as core.String
            : null,
        optimizationStrategy: json_.containsKey('optimizationStrategy')
            ? json_['optimizationStrategy'] as core.String
            : null,
        optimizer: json_.containsKey('optimizer')
            ? json_['optimizer'] as core.String
            : null,
        pcaExplainedVarianceRatio:
            json_.containsKey('pcaExplainedVarianceRatio')
                ? (json_['pcaExplainedVarianceRatio'] as core.num).toDouble()
                : null,
        pcaSolver: json_.containsKey('pcaSolver')
            ? json_['pcaSolver'] as core.String
            : null,
        sampledShapleyNumPaths: json_.containsKey('sampledShapleyNumPaths')
            ? json_['sampledShapleyNumPaths'] as core.String
            : null,
        scaleFeatures: json_.containsKey('scaleFeatures')
            ? json_['scaleFeatures'] as core.bool
            : null,
        standardizeFeatures: json_.containsKey('standardizeFeatures')
            ? json_['standardizeFeatures'] as core.bool
            : null,
        subsample: json_.containsKey('subsample')
            ? (json_['subsample'] as core.num).toDouble()
            : null,
        tfVersion: json_.containsKey('tfVersion')
            ? json_['tfVersion'] as core.String
            : null,
        timeSeriesDataColumn: json_.containsKey('timeSeriesDataColumn')
            ? json_['timeSeriesDataColumn'] as core.String
            : null,
        timeSeriesIdColumn: json_.containsKey('timeSeriesIdColumn')
            ? json_['timeSeriesIdColumn'] as core.String
            : null,
        timeSeriesIdColumns: json_.containsKey('timeSeriesIdColumns')
            ? (json_['timeSeriesIdColumns'] as core.List)
                .map((value) => value as core.String)
                .toList()
            : null,
        timeSeriesLengthFraction:
            json_.containsKey('timeSeriesLengthFraction')
                ? (json_['timeSeriesLengthFraction'] as core.num).toDouble()
                : null,
        timeSeriesTimestampColumn:
            json_.containsKey('timeSeriesTimestampColumn')
                ? json_['timeSeriesTimestampColumn'] as core.String
                : null,
        treeMethod: json_.containsKey('treeMethod')
            ? json_['treeMethod'] as core.String
            : null,
        trendSmoothingWindowSize:
            json_.containsKey('trendSmoothingWindowSize')
                ? json_['trendSmoothingWindowSize'] as core.String
                : null,
        userColumn: json_.containsKey('userColumn')
            ? json_['userColumn'] as core.String
            : null,
        vertexAiModelVersionAliases:
            json_.containsKey('vertexAiModelVersionAliases')
                ? (json_['vertexAiModelVersionAliases'] as core.List)
                    .map((value) => value as core.String)
                    .toList()
                : null,
        walsAlpha: json_.containsKey('walsAlpha')
            ? (json_['walsAlpha'] as core.num).toDouble()
            : null,
        warmStart: json_.containsKey('warmStart')
            ? json_['warmStart'] as core.bool
            : null,
        xgboostVersion: json_.containsKey('xgboostVersion')
            ? json_['xgboostVersion'] as core.String
            : null,
      );