[MQL5] Clarification on loss visualization in gradient descent

Clarification on loss visualization in gradient descent: a 2D curve plot does not imply a unique minimum error. The loss

An update to a single-neuron gradient-descent implementation adds a bias term. Weight and bias gradients differ, so the loss function must return two doubles; a struct-based return is one practical approach in MQL5. Stochastic gradient descent is outlined as a performance variant…

• 출처: MQL5 아티클

MQL5 공식 사이트에 올라온 새 아티클이에요. EA 개발·백테스트·전략 공부에 도움이 돼요. 주소의 /en/ 을 /ko/ 로 바꾸면 한국어판이 있는 글도 있어요.