📄 中文摘要
研究表明，80%的机器学习项目因问题框架不当而失败，而非模型表现不佳。因此，在编写训练代码之前，定义正确的问题至关重要。提出了一种五步协议，帮助从业者更有效地识别和界定问题。这一过程包括明确目标、理解数据、识别约束、制定评估标准以及选择合适的模型。通过遵循这一协议，能够提高项目成功的可能性，确保资源的有效利用。
停止调整超参数，开始调整问题
出处: Stop Tuning Hyperparameters. Start Tuning Your Problem.
发布: 2026年3月4日
📄 English Summary
Stop Tuning Hyperparameters. Start Tuning Your Problem.
Research indicates that 80% of machine learning projects fail due to poor problem framing rather than inadequate models. Defining the right problem is crucial before writing training code. A five-step protocol is proposed to help practitioners effectively identify and define the problem. This process includes clarifying objectives, understanding data, identifying constraints, establishing evaluation criteria, and selecting appropriate models. By following this protocol, the likelihood of project success can be increased, ensuring efficient use of resources.