Data Science Statistics
A test set is a subset of data used to evaluate the performance of a machine learning model after it has been trained on a training set. It helps to provide an unbiased assessment of the model's predictive capability, indicating how well it can generalize to unseen data. The test set plays a critical role in understanding the model's effectiveness and helps in balancing the tradeoff between bias and variance.
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