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Question & Answer
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To ensure data integrity
To simplify the training process
To maintain input-output relationships
To enhance model interpretability
Understanding the Answer
Let's break down why this is correct
Identity mapping keeps the input and output in the same form. Other options are incorrect because Some think identity mapping keeps data unchanged, but it is not about data integrity; People may think identity mapping makes training easier, but it does not simplify the learning process.
Key Concepts
Identity Mapping in Deep Models
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Deep Dive: Identity Mapping in Deep Models
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Definition
Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.
Topic Definition
Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.
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