What is a wide model?
A linear model that typically has many sparse input features.
wide model explained in plain English
A linear model that typically has many sparse input features. We refer to it as "wide" since such a model is a special type of neural network with a large number of inputs that connect directly to the output node. Wide models are often easier to debug and inspect than deep models. Although wide models cannot express nonlinearities through hidden layers, wide models can use transformations such as feature crossing and bucketization to model nonlinearities in different ways. Contrast with deep model.
Example
Practitioners refer to wide model when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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