Incremental
Incremental refers to the process of continuously adding new data to an existing dataset or model, in order to improve its accuracy and performance over time. This approach is commonly used in machine learning and data mining, where models are trained on large datasets and then updated with new data as it becomes available. Incremental learning allows models to adapt to changing conditions and new information, without requiring a complete retraining of the model. This can save time and resources, and also allows models to be more responsive to real-time data. Incremental learning can also refer to the process of gradually increasing the complexity of a model, by adding new features or layers, in order to improve its accuracy and performance.
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