有没有办法使用curl命令来训练时间序列GoogleAutoML表模型？

下面给出的JSON文件是request.JSON，用于使用Google AutoML表训练分类或回归模型

{
  "datasetId": "dataset-id",
  "displayName": "model-display-name",
  "tablesModelMetadata": {
    "trainBudgetMilliNodeHours": "train-budget-milli-node-hours",
    "optimizationObjective": "optimization-objective",
    "targetColumnSpec": {
      "name": "projects/project-id/locations/location/datasets/dataset-id/tableSpecs/table-id/columnSpecs/target-column-id"
    }
  },
}

我需要通过在json文件中提供“time series Identifier”列和“Forecast Horizon”来使用curl命令训练时间序列模型。所以我理想的请求文件应该是

{
  "datasetId": "dataset-id",
  "displayName": "model-display-name",
  "tablesModelMetadata": {
    "trainBudgetMilliNodeHours": "train-budget-milli-node-hours",
    "optimizationObjective": "optimization-objective",
    "forecastHorizon": "horizon",
    "timeseriesIdentifier":"column-id",
    "targetColumnSpec": {
      "name": "projects/project-id/locations/location/datasets/dataset-id/tableSpecs/table-id/columnSpecs/target-column-id"
    }
  },
}

这样我就可以使用以下命令传递上面给出的request.json文件

curl -X POST \
-H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
https://endpoint/v1beta1/projects/project-id/locations/location/models/

---

有什么方法可以做到这一点吗？

目前，Cloud Auto ML表提供了回归或分类问题

你应该考虑BigQualML创建一个模型语句，你可以使用它在CURL命令中传递参数“TimeSeriSeIdStand”和“ValeX”。 JSON表示

{
  "trainingOptions": {
    {
     "maxIterations": string,
     "lossType": enum (LossType),
     "learnRate": number,
     "l1Regularization": number,
     "l2Regularization": number,
     "minRelativeProgress": number,
     "warmStart": boolean,
     "earlyStop": boolean,
     "inputLabelColumns": [
       string
     ],
     "dataSplitMethod": enum (DataSplitMethod),
     "dataSplitEvalFraction": number,
     "dataSplitColumn": string,
     "learnRateStrategy": enum (LearnRateStrategy),
     "initialLearnRate": number,
     "labelClassWeights": {
       string: number,
       ...
     },
     "userColumn": string,
     "itemColumn": string,
     "distanceType": enum (DistanceType),
     "numClusters": string,
     "modelUri": string,
     "optimizationStrategy": enum (OptimizationStrategy),
     "hiddenUnits": [
       string
     ],
     "batchSize": string,
     "dropout": number,
     "maxTreeDepth": string,
     "subsample": number,
     "minSplitLoss": number,
     "numFactors": string,
     "feedbackType": enum (FeedbackType),
     "walsAlpha": number,
     "kmeansInitializationMethod": enum (KmeansInitializationMethod),
     "kmeansInitializationColumn": string,
     "timeSeriesTimestampColumn": string,
     "timeSeriesDataColumn": string,
     "autoArima": boolean,
     "nonSeasonalOrder": {
       object (ArimaOrder)
     },
     "dataFrequency": enum (DataFrequency),
     "includeDrift": boolean,
     "holidayRegion": enum (HolidayRegion),
     "timeSeriesIdColumn": string,
     "horizon": string,
     "preserveInputStructs": boolean,
     "autoArimaMaxOrder": string
   }
     },
  "startTime": string,
  "results": [
    {
      object (IterationResult)
    }
  ],
  "evaluationMetrics": {
    object (EvaluationMetrics)
  },
  "dataSplitResult": {
    object (DataSplitResult)
  }
}

Curl命令：

curl \
  'https://bigquery.googleapis.com/bigquery/v2/projects/YOUR_PROJECT/model/YOUR_MODEL?key=[YOUR_API_KEY]' \
  --header 'Authorization: Bearer [YOUR_ACCESS_TOKEN]' \
  -d @request.json \ \
  --compressed