What is gradient descent in classification training?
Updated May 15, 2026
Short answer
Gradient descent is an optimization method used to minimize classification loss.
Deep explanation
It iteratively updates model parameters in the direction of negative gradients of a loss function like cross-entropy.
Real-world example
Training logistic regression or neural networks.
Common mistakes
- Using too large learning rates causing divergence.
Follow-up questions
- What is learning rate?