Data Science Asked by developer1 on April 3, 2021
I have no experience in statistics or machine learning. I have a True/False binary array describing occupation of open public spaces
+---------------------+
| index | Value |
+---------------------+
| 0 | True |
| 1 | True |
| 2 | False |
| 3 | False |
| 4 | False |
| 5 | True |
| 6 | False |
| 7 | False |
| 8 | True |
| ... | ... |
+---------------------+
Without getting into dependent variables and domain specific heuristics, is there (or maybe more than one) a simple method to do infer the next False in python?
Ideally in pure python or using packages written in pure python.
My question is somewhat similar to this one, but I have more of a time series (i think).
Do you have more features ? If not, you can try to find a filling pattern, for example, probably some places are filled first because, for example, are closer to the entrance, then another group etc. Try to plot as a time dependent problem. I cannot tell how much bigger the error will be. If you have at least the x, y of the place and the timestep of the value, then you have a pattern.
Answered by Eduardo Di Santi Grönros on April 3, 2021
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