I have data on visits to a number of pages, the last 30 days. Looks something like this:
Page 1: [1,2,0,4,6,1,7,4,7]
Page 2: [3,4,12,1,7,1,2,0]
These pages very much. I need to isolate the pages that felt unusual inflow or outflow of users at any given time. What algorithm or sequence of algorithms suitable for this task best?
UPD: while looking at the machine learning algorithm anomalies detection, but maybe there's a way to quickly, for example (thinking out loud) can break the data sets into several equal parts and compare them to interest fluctuations. If all in the range 0, then we can assume that there are no abnormalities, the leap - then something went wrong. Most likely, it will do.