What defines sequence data in the context of machine learning?

Sequence data in machine learning pertains to data where the order of the elements is significant. This characteristic is crucial because many processes, decisions, or outcomes depend not just on the individual data points but on how they relate to one another in a specific sequence. For instance, in time series analysis, the value of a data point may depend on previous values, making the sequence essential for modeling and prediction.

When dealing with natural language processing, the order of words affects meaning, highlighting the importance of sequence in interpreting data correctly. Other applications, such as analyzing video frames or predicting stock prices over time, also rely on the sequential nature of data to achieve accuracy in predictions or insights. Thus, emphasizing the relevance of both order and context in the interpretation and utilization of sequence data is fundamental in various machine learning scenarios.