[IDEA] Chapter 3: 90% recall classifier

In chapter 3 (p, 96) see how a 90% precision classifier can be created.

What about a 90% recall classifier?

One would be tempted to do (at least I was)

```
threshold_90_recall = thresholds[np.argmax(recalls >= 0.90)]
```

but a simple

```
recalls[np.argmax(recalls >= 0.90)] # result 1.0
```

would demonstrate that it's not correct.

I've tried different solutions and this is the most elegant/concise I came up with

```
threshold_90_recall[len(recalls) - np.argmax(recalls[::-1] >= 0.90) - 1]
```