JoshuaC3

This would be great to have as an IPython notebook. IMO the more examples the better. If I find time I can do one.

I'll take a look at it and do a PR at some point.

@janmotl that is a really nice idea. This does add a fair bit of complexity though. I am a bit of a newb here and this seems a little complex...

@jkleint @janmotl personally, I don't feel this is the correct way to do this. I think we should be treating a single column in an array or dataframe as the...

@janmotl I have started this. Yes, I see that `ascending` is not as intuitive as I first though. Would be good to hear if there are any better key names...

Once the standard CountEncoding is implemented we can also include kwargs [`log_transform=True`](https://www.slideshare.net/HJvanVeen/feature-engineering-72376750/11) and [`label_count_ranking=True`](https://wrosinski.github.io/fe_categorical_encoding/).

@janmotl Very happy to take a look at this.

> > Is it possible to make a conceptual drawing of this? Jjust make sure we'll be talking about the same thing, I often find pictures say more than words....

FYI another possibility for multiple seasonality: https://robjhyndman.com/papers/multiseasonal.pdf Admittedly, this seems rather more complex but could be useful.

I think a verbose setting such as `verbose=0/None` gives no output and `verbose=100` prints every 100th round would be sufficient. This the general behaviour of the "Big Three" GBM models....