This endpoint is in preview and may be modified or removed at any time.
To use this endpoint, add preview=true to the request query parameters.
Lists all available trainers for Model Studios.
Third-party applications using this endpoint via OAuth2 must request the following operation scope: api:models-read.
objectlist<ModelStudioTrainer>optional1
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curl \
\t-H "Authorization: Bearer $TOKEN" \
"https://$HOSTNAME/api/v2/models/modelStudioTrainers?preview=true"1
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{
"data": [
{
"outputs": {
"model": {
"name": "Output model",
"optional": false,
"type": {
"type": "model",
"model": {
"modelApiAliases": [
{
"alias": "input_df",
"description": "Input dataset"
},
{
"alias": "output_df",
"description": "Output dataset"
}
]
}
}
}
},
"customConfigSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"title": "AutoGluonTabularRegressionConfig",
"type": "object",
"additionalProperties": false,
"properties": {
"eval_metric": {
"title": "Evaluation metric",
"default": "mean_squared_error",
"$ref": "#/$defs/RegressionMetricType"
},
"presets": {
"title": "Training presets",
"default": "medium_quality",
"$ref": "#/$defs/PresetsType"
},
"refit_full": {
"title": "Refit on full data",
"description": "After evaluation, refit the best model on the combined training and test data.",
"type": "boolean",
"default": false
}
},
"$defs": {
"PresetsType": {
"title": "PresetsType",
"description": "Pre-built training presets",
"oneOf": [
{
"type": "string",
"const": "best_quality",
"description": "Best predictive accuracy, at the cost of training and inference speed."
},
{
"type": "string",
"const": "medium_quality",
"description": "Medium predictive accuracy with very fast inference and very fast training time."
}
]
},
"RegressionMetricType": {
"title": "RegressionMetricType",
"description": "The metric to optimize for when selecting the best model.",
"oneOf": [
{
"type": "string",
"const": "root_mean_squared_error",
"description": "Measures the square root of the average squared differences between predicted and actual values."
},
{
"type": "string",
"const": "mean_squared_error",
"description": "The average of the squared differences between predicted and actual values."
}
]
}
}
},
"inputs": {
"input_df": {
"name": "Training dataset",
"description": "Input dataset for training. If no testing dataset is provided, 20% of this dataset will be held out as a test dataset for evaluation.",
"optional": false,
"type": {
"type": "dataset",
"dataset": {
"role": "TRAINING",
"columnsTypeSpecs": {
"target_column": {
"name": "Target column",
"isTarget": true,
"allowMultiple": false,
"optional": false,
"supportedTypes": [
{
"type": "grouped",
"grouped": "NUMERIC"
}
]
}
}
}
}
},
"test_df": {
"name": "Test dataset",
"description": "Input dataset for testing. Used for evaluating the best model only.",
"optional": true,
"type": {
"type": "dataset",
"dataset": {
"role": "TEST",
"columnsTypeSpecs": {}
}
}
}
},
"name": "AutoGluon Tabular Regression Trainer",
"description": "Regression with AutoGluon TabularPredictor",
"experimental": false,
"type": "GENERIC",
"version": "0.388.0",
"trainerId": "ri.models..trainer.autogluon_tabular_regression"
}
]
}