Western Governors University (WGU) MATH1200 C957 Applied Algebra Practice Exam

The term that refers to a model's ability to accurately predict outcomes based on the data it was created from is model accuracy. This concept encompasses how well the predictions of the model align with the actual outcomes in the dataset. High model accuracy indicates that the model has effectively learned the underlying patterns present in the data and can generalize well to new, unseen data.

Model accuracy is typically quantified using various metrics, such as the proportion of true results among the total number of cases examined. In contrast, outlier detection refers to identifying data points that differ significantly from the rest of the dataset, while sample effectiveness does not specifically address prediction capabilities. Extrapolated potential involves extending predictions beyond the range of the dataset, which is different from measuring how well the model predicts within the original dataset. Hence, the focus on prediction and alignment with actual outcomes makes model accuracy the correct term.

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