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0.5814568701544718, 0.6651538910132964, 0.3138080342665499
0.6711642728531724, 0.7466687034026017, 0.1215477472819713
0.0453256543003371, 0.6377430803264152, 0.3558625219713576
0.4785191813363956, 0.0265841045263860, 0.0376935084990697

1, 0.5385257417814224

{
                    
    "headers": [
        "feature_1",
        "feature_2",
        "feature_3"
    ],
    "methods": {
        "shap": {
            "baseline": [
                [0.4441164946610942, 0.5190374448171748, 0.20722795300473712]
            ],
            "num_samples": 100,
            "agg_method": "mean_abs"
        }
    },
    "predictor": {
        "model_name": "my_model",
        "instance_type": "ml.m5.xlarge",
        "initial_instance_count": 1
    }
}

"EndpointInput": {
    ...
    "ProbabilityAttribute": 1
    ...
}

{"features":[0, 0.5814568701544718, 0.6651538910132964, 0.3138080342665499], "label":0}
{"features":[1, 0.6711642728531724, 0.7466687034026017, 0.1215477472819713], "label":1}
{"features":[0, 0.0453256543003371, 0.6377430803264152, 0.3558625219713576], "label":1}
{"features":[1, 0.4785191813363956, 0.0265841045263860, 0.0376935084990697], "label":1}

{"predicted_label":1, "probability":0.5385257417814224}

{
    "headers": [
        "feature_1",
        "feature_2",
        "feature_3"
    ],
    "methods": {
        "shap": {
            "baseline": [
                {"features":[0.4441164946610942, 0.5190374448171748, 0.20722795300473712]}
            ],
            "num_samples": 100,
            "agg_method": "mean_abs"
        }
    },
    "predictor": {
        "model_name": "my_model",
        "instance_type": "ml.m5.xlarge",
        "initial_instance_count": 1,
        "content_template":"{\"features\":$features}"
    }
}

"EndpointInput": {
    ...
    "FeaturesAttribute": "features",
    "ProbabilityAttribute": "probability",
    ...
}