TensorFlow in keras The built-in optimizer of the module has?

Question

Options

• AAdam
• BSGD
• CAdaboost
• DAdadelta

• A
  100% (19)

Explanation

Adam (A), SGD (B), and Adadelta (D) are all genuine built-in Keras optimizers - found in tf.keras.optimizers - used to update model weights during training via gradient descent variants. However, Adaboost (C) is not a Keras optimizer at all; it is an ensemble machine learning method (Adaptive Boosting) that combines weak classifiers and has no role in neural network weight updates. The stated answer of "all of the above" appears to be an error in the question - the defensible correct answer is A, B, and D.

Why each option matters:

• Adam - combines momentum and adaptive learning rates; the most popular default optimizer.
• SGD - the foundational gradient descent method, optionally with momentum.
• Adadelta - adapts learning rates per parameter without needing a global rate; a Keras built-in.
• Adaboost - belongs to ensemble/boosting methods (think sklearn), not neural network optimizers.

Memory tip: To recall Keras optimizers, remember the prefix "Ada" - Adagrad, Adadelta, Adam, Adamax are all Keras optimizer family members. Adaboost breaks the pattern because it is a boosting algorithm, not a gradient-based optimizer - if you see "boost" in the name, think ensemble method, not Keras.

No community discussion yet for this question.