What is the reason for doing shift for the features (1 timestep) ?

[bernardoleite]

Hi there! Thanks for your implementation.

I would like to clarify a doubt, if possible. From the data_util.py file we can observe:

# Step 4 - Convert to a sequence per user id and shift features 1 timestep
seq = df.groupby('user_id').apply(
    lambda r: (
        r['skill_with_answer'].values[:-1],
        r['skill'].values[1:],
        r['correct'].values[1:],
    )
)

I could not understand the reason for making that shift. Can you clarify?
Thanks in advance.

[Blackbird95x]

Hey there! i currently working on my Implementation, my first ever ML model ever, and im glad Mr. Cassagrande did an amazing Job on his implementation. Thats why I try to understand and get it to my use case. but I cant wrap my head arround it. I dont quite understand why you would drop a datapoint. Maybe you got some clarity over the problem over the time and would help me to understand