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已经非常接近真实值了，如果继续微调，就可以无限接近真实值，虽然一般无法求得最优解，但现实中只是误差可以接受就可以了。通过现有的数据或资料，称为样本，通过尝试求解参数（局部最优解）的过程，就是机器学习的核心内容。误差值是用来控制每次调整参数的幅度。

打开交易图表，堆上十个技术指标，然后对着屏幕发呆不知道下一步怎么操作——这场景对交易员来说太熟悉了。如果把历史数据丢给计算机，告诉它“去试错”。赚了有奖励，亏了有惩罚。让它在不断的尝试和失败中学习，最终迭代出一个不说完美、但至少能逻辑自洽的交易策略。

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