Linear Learner Response Formats

All Amazon SageMaker built-in algorithms adhere to the common input inference format described in Common Data Formats - Inference. The following are the available output formats for the Amazon SageMaker linear learner algorithm.

Binary Classification

let response =   {
    "predictions":    [
        {
            "score": 0.4,
            "predicted_label": 0
        } 
    ]
}

Multiclass Classification

let response =   {
    "predictions":    [
        {
            "score": [0.1, 0.2, 0.4, 0.3],
            "predicted_label": 2
        } 
    ]
}

Regression

let response =   {
    "predictions":    [
        {
            "score": 0.4
        } 
    ]
}

Binary Classification

{"score": 0.4, "predicted_label": 0}

Multiclass Classification

{"score": [0.1, 0.2, 0.4, 0.3], "predicted_label": 2}

Regression

{"score": 0.4}

Binary Classification

[
    Record = {
        features = {},
        label = {
            'score’: {
                keys: [],
                values: [0.4]  # float32
            },
            'predicted_label': {
                keys: [],
                values: [0.0]  # float32
            }
        }
    }
]

Multiclass Classification

[
    Record = {
    "features": [],
    "label":    {
            "score":  {
                    "values":   [0.1, 0.2, 0.3, 0.4]   
            },
            "predicted_label":  {
                    "values":   [3]
            }
       },
    "uid":  "abc123",
    "metadata": "{created_at: '2017-06-03'}"
   }
]

Regression

[
    Record = {
        features = {},
        label = {
            'score’: {
                keys: [],
                values: [0.4]  # float32
            }   
        }
    }
]