Daily Productive Sharing 425 - How to Deal With 80/20 Rule?
One helpful tip per day:)
(下附中文版)
Pareto's law, also known as the 80/20 rule or the power law, is a law that we often encounter in life, such as 80% of wealth being owned by 20% of the population and the remaining 20% being owned by the remaining 80%. Although it seems to be a law that we are familiar with, Ben Kuhn details how to understand it and how to optimise its output in our life:
- Because heavy-tailed distributions are unintuitive, people often make serious mistakes when trying to sample from them:
- They don’t draw enough samples
- They underestimate how good of an outcome it’s possible to get
- They find it hard to tell whether they’re following a strategy that will eventually work or not, so they get incredibly demoralized
- The most important thing to remember when sampling from heavy-tailed distributions is that getting lots of samples improves outcomes a ton.
- This means that sampling from a heavy-tailed distribution can be extremely demotivating, because it requires doing the same thing, and watching it fail, over and over again.
- An important thing to remember in this case is to trust the process and not take individual failures, or even large numbers of failures, as strong evidence that your overall process is bad.
- Some amount of optimization is worth it, but most people are way over-indexed on optimization and under-indexed on drawing more samples.
- One thing helpful is to ask other people what outliers have looked like based on their experience.
- So what does a good process for searching for outliers look like?
- Take lots of shots on goal. The more samples you have, the more likely you’ll find an outlier.
- Know what to look for: try to figure out how good of an outcome is possible, so you know when to stop.
- Find ways to evaluated candidates that are well-correlated with what you care about. Filter for “maybe amazing,” not “probably good.”
- When possible, try to sample and evaluate candidates quickly, so that you can iterate on your sampling process more quickly.
- Don’t get discouraged when you do the same thing over and over again and it mostly doesn’t work!
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帕累托定律，又称为80/20法则或者幂定律，是我们在生活经常遇见的定律，比如80%的财富被20%的人拥有，而剩下的20%被其余的80%人拥有。尽管这似乎是我们熟知的一个定律，但是 Ben Kuhn 详细介绍了如何理解这一定律，并在生活中如何优化这一定律的产出：
由于长尾分布并不直观，人们在试图取样时经常会犯严重错误。
- 他们没有抽取足够的样本
- 他们低估了可能得到美好结果的可能性
- 他们发现很难判断自己的策略是否有效，所以他们会感到非常沮丧。
- 从长尾分布中取样时，最重要的一点是，获得大量的样本可以大大改善结果。
- 在这种情况下，需要记住的一件事是相信这个过程，不要把个别的失败，当作整体过程不好的证据。
- 一定量的优化是值得的，但大多数人对优化的重视程度过高，而对抽取更多样本的重视程度不足。
询问他人，在他们的眼中，异常值是什么的：
- 你的样本越多，你就越有可能发现异常值。
- 知道要找的是什么：试着弄清楚美好结果是可能的，这时你就知道该收手了。
- 建立一套评估方法，可以找出与你关心的相关联的候选。筛选出 "可能很好"，而不是 "可能还好"。
- 在可能的情况下，尽量快速地对候选人进行评估，这样你就能更快地迭代你的采样过程。
- 当你一遍又一遍地做同样的事情，但大部分情况下都不奏效时，不要感到气馁。
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