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training set
This term is a technical staple of machine learning and statistics. It refers specifically to the initial data used to fit a model, distinguishing it from a validation set or a test set. Using the wrong set for the wrong purpose, such as testing a model on its training set, leads to overfitting, where the model memorizes data rather than learning general patterns.
In professional contexts, the term is almost always used in contrast with other data partitions. While a training set provides the ground truth for learning, the test set provides the unbiased evaluation of the final model's performance.
Meanings
Examples
The model performed well on the training set but failed on new data.
We need a larger training set to improve the accuracy of the classifier.
I wonder if the training set contains enough diverse examples.
Make sure you shuffle the training set before starting the process.
The training set was split into several smaller batches for efficiency.
Is the training set properly labeled for this task?
Overfitting occurs when the model learns the training set too perfectly.