Hi, can someone explain me what’s means “true mean consumption over the prediction window under consideration” in the metric description? Thanks!

Take for example `series_id = 100454`

. Each measurement of consumption is made hourly in `cold_start_test.csv`

and you have to predict the consumption for a week. As you can see (in `submission_format.csv`

), the `prediction_window`

says `daily`

, which means that the number you insert there is the consumption on that day

```
7021 100454 2016-03-22 00:00:00 14.805556 0 daily
```

Of course, you don’t know that number. Let’s say that the model predicts a consumption of 124568 watt-hours, but the real number is 541268 watt-hours. The number 541268 is *the true mean consumption over the prediction window under consideration*.

As you may know now, the measurement (in `consumption_train.csv`

) is almost always (I’d say always) made hourly, so in this case, on `2016-03-22`

, maybe the model predicts a consumption every hour (24 in total), but you have to sum those 24 measurements and insert the number there

```
7021 100454 2016-03-22 00:00:00 14.805556 124568 daily
```

Yes, I said *have to sum* instead of *take the mean* because “we include a `prediction_window`

column to help indicate what level of temporal **aggregation** we want you to predict.” Aggregation means sum.

I hope I am not mistaken about this.