Unlabeled Data

In the context of data science, unlabeled data refers to a dataset that does not have any predefined categories or labels. This means that the data has not been classified or organized in any way that would allow a machine learning algorithm to learn from it. Unlabeled data is often used in unsupervised learning, where the goal is to identify patterns or relationships within the data without any prior knowledge of what those patterns might be. Unlabeled data can also be used in semi-supervised learning, where a small amount of labeled data is combined with a larger amount of unlabeled data to improve the accuracy of a machine learning model. Unlabeled data can come from a variety of sources, including user behavior data, sensor data, and text data.
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