BCreating a dataset for the machine-learning-model

A properly created dataset is a basis for machine learning models that will allow you to create predictions in the beqom application. The POST /api/v{version}/Dataset endpoint creates a new dataset and t accepts a dataset configuration and returns an ID for the newly created dataset.

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For more information about using beqom API please, see A beginner's guide to using beqom APIs

:

Parameters:

version (string): The version of the API.

Request Body:

{

"name": "string",

"description": "string",

"label": "string",

"applyCurrency": true,

"applyFte": true,

"applyLog": true,

"fields": [

"string"

]

}

Where:

• name - the name of the dataset.

  description - brief description of the dataset.

• label - the field on which the user wants to make predictions (e.g., salary).

• applyCurrency - indicates whether to apply currency normalization.

• applyFte: - indicates whether to apply Full-Time Equivalent (FTE) adjustments.

• applyLog - indicates whether to apply logarithmic transformation.

• fields - an array of fields on which the user wants to train the model.

Responses:

• 200 OK - successfully created the dataset.

  {

  "id": "3fa85f64-5717-4562-b3fc-2c963f66afa6"

  }

• 400 Bad Request - returned if the request body is invalid or missing required fields.

• 403 Forbidden - returned if the user does not have permission to access the datasets.

• 500 Internal Server Error - returned if there is a server-side error while processing the request.