Model output is the prediction or decision made by a machine learning model based on input data.
In supervised learning, the model output is a predicted target value for a given input. In unsupervised learning, the model output may include cluster assignments or other learned patterns in the data.
Model output can be a single value, a probability distribution, a class label, or a series of continuous or discrete values, and is often used to evaluate the performance of a machine learning model.
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