Structuring Machine Learning Projects-Week2
Week2 1. Carrying out error analysis 对已经建立的机器学习模型进行错误分析（error analysis）十分必要，而且有针对性地、正确地进行error analysis更加重要。 举个例子，猫类识别问题，已经建立的模型的错误率为10%。为了提高正确率，我们发现该模型会将一些狗类图片错误分类成猫。一种常规解决办法是扩大狗类样本，增强模型对够类（负样本）的训练。但
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相关文章
- 1. Structuring Machine Learning Projects-Week1
- 2. COURSE 3 Structuring Machine Learning Projects
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