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Thanks for using SageMaker. The scores returned by multiclass models are the predicted probabilites for each class.
In your first example, the model is predicting class 1 with 81% confidence, and in your second example, the model is predicting class 2 with 87% confidence.
In general, to interpret the score
from classification models, you have to consider the loss function. If the loss is logistic
for binary classification or softmax_loss
for multiclass classification, then the score
can be interpreted as a probability. These are the default losses used by Linear Learner. But if the loss is hinge_loss
, then the score
cannot be interpreted as a probability. This is because hinge loss corresponds to a Support Vector Classifier, which does not produce probability estimates.
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