Labeled Data
Labeled data is a type of data that has been tagged with one or more labels, or categories, that identify the characteristics of the data. In the context of data science and artificial intelligence, labeled data is used to train machine learning models to recognize patterns and make predictions. Labeled data is often created through a process called annotation, in which humans manually assign labels to data based on specific criteria. This process can be time-consuming and expensive, but it is necessary for many machine learning applications, such as image recognition, natural language processing, and sentiment analysis. Labeled data is also important for evaluating the accuracy of machine learning models, as it provides a benchmark for comparison.
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