Training set, in the context of artificial intelligence and machine learning, refers to a data set that is used to train a machine learning model or algorithm.
The training set consists of a set of labelled examples, where each example includes features (also known as independent variables or predictors) and a label (also known as a dependent or target variable). The machine learning model uses the training set to learn to relate input features to output labels, so that it can generalise to predict output labels for new examples.
The training set is a critical component of the machine learning process, as the quality and quantity of the training data influences the accuracy of the resulting model.
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