adaptiveCategory
AdaptiveCategory is a concept in the field of machine learning and data science that refers to the dynamic classification or categorization of data based on evolving patterns and characteristics. Unlike traditional static categorization methods, which rely on predefined rules or fixed criteria, AdaptiveCategory employs algorithms that can learn and adapt to changes in the data over time. This adaptability is crucial in environments where data distributions shift, new categories emerge, or existing ones evolve, ensuring that the categorization remains accurate and relevant.
The core principle behind AdaptiveCategory is the use of machine learning models that can update their parameters
One of the key advantages of AdaptiveCategory is its ability to handle non-stationary data, where the statistical
However, the adaptability of AdaptiveCategory also introduces challenges, such as the risk of overfitting to recent