Training Dataset

A training dataset contains examples that a model uses to learn how to perform a specific task. Depending on the learning approach, the data may include labels, such as categories or target values, or may consist primarily of unlabeled examples. The quality, size, diversity, and relevance of the dataset can strongly affect model performance.

A well-designed training dataset helps a model learn useful and representative patterns while reducing problems such as bias, noise, and poor generalization. If the training data is incomplete, inaccurate, or unrepresentative, the resulting model may perform poorly or reproduce unwanted patterns.