Cascademodel
The Cascademodel is a machine learning framework designed for processing sequential data, particularly in areas like natural language processing and speech recognition. Its core principle involves breaking down complex tasks into a series of interconnected stages or "cascades." Each stage in the cascade takes the output of the previous stage as its input and performs a specific, often simpler, processing step. This hierarchical structure allows for a modular and interpretable approach to modeling.
In practice, a Cascademodel might consist of multiple layers, where each layer learns to refine or transform
The training of a Cascademodel typically involves optimizing each stage sequentially or jointly, depending on the