Dears,
I have data for customer visits in mall which the first column is unique user identifier. The second column if indices of a day when customer have visited a mall. Enumeration is started from some fixed day; the day with index 1 is Monday (e. g. 7th is Sunday, 8th is again Monday). Indices are in the range from 1 to 1001 which equals to 143 full weeks. You are to predict the first day of the next (144th) week when user will visit a mall. For example, if a user will visit a mall on Wednesday of the next week, then your prediction should be equal to 3. So for each user, you need to predict a number: ● 0: no visit on the next week ● 1: Monday ● 2: Tuesday ● 3: Wednesday ● 4: Thursday ● 5: Friday ● 6: Saturday ● 7: Sunday
the sample of data is:
User_id, Visits 1,30 84 126 135 137 179 242 342 426 456 460 462 483 594 600 604 704 723 744 787 804 886 924 928 946 954 2,24 53 75 134 158 192 194 211 213 238 251 305 404 418 458 476 493 571 619 731 739 759 761 847 883 943 962 981 983
and I have the actual visits as
user_id, Next_visit_day
1,3
2,4
How to resolve the issue in order to get the best accurate model, which nodes or techniques to handle this type of problem.
I appreciate your support
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