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.
: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.