Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

The data preparation question #7

Open
ggeeoorrgg opened this issue Apr 27, 2023 · 0 comments
Open

The data preparation question #7

ggeeoorrgg opened this issue Apr 27, 2023 · 0 comments

Comments

@ggeeoorrgg
Copy link

As stated in the book's Chapter 10 "...The exact formulation of the problem will be as follows: given data covering the previous five days and sampled once per hour, can we predict the temperature in 24 hours?.."
With this in mind do we really need to subtract 1 in :
delay <- sampling_rate * (sequence_length + 24 - 1)? (see row #108 Ch 10).
I know, this code matches the book.
But for this delay the 1st sample:

> full_df$`Date Time`[1]
[1] "2009-01-01 00:10:00 -01"

has such target:

> head(tail(full_df$`Date Time`, -delay),1)
[1] "2009-01-06 23:10:00 -01"

It is not exactly 24 hours for a prediction horizon.
Without subtracting 1 things seem to look better:

delay <- sampling_rate * (sequence_length + 24)
head(tail(full_df$`Date Time`, -delay),1)
[1] "2009-01-07 00:10:00 -01"

So i can`t figure out the reason for subtracting of 1.
Any thoughts?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant