What is a discriminator?
A system that determines whether examples are real or fake.
discriminator explained in plain English
A system that determines whether examples are real or fake. Alternatively, the subsystem within a generative adversarial network that determines whether the examples created by the generator are real or fake. See The discriminator in the GAN course for more information.
Example
Practitioners refer to discriminator when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
People also read
- generative adversarial network
A system to create new data in which a generator creates data and a discriminator determines whether that created data is valid or invalid.
- generative model
Practically speaking, a model that does either of the following: - Creates (generates) new examples from the training dataset.
- generator
The subsystem within a generative adversarial network that creates new examples.
- model
In general, any mathematical construct that processes input data and returns output.
- accelerator chip
A category of specialized hardware components designed to perform key computations needed for deep learning algorithms.
- activation function
A function that enables neural networks to learn nonlinear (complex) relationships between features and the label.
- AdaGrad
A sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving each parameter an independent learning rate.
- Attention
A mechanism that lets a model focus on the most relevant parts of its input when producing an output, weighting what matters most in context.
- attribute
Synonym for feature.
- auto-regressive model
A model that infers a prediction based on its own previous predictions.