I think it might be a good idea to come up with a method to relax the Matrix Profile. (I have been thinking about this idea for a while. I haven't got any conclusion yet. I am still thinking about it and I thought it might be a good idea to share it.
By the term "relax", I mean to consider close neighbors and not just closest data point. For instance, let's say we have seven data points where each data point is a Time Series of length two as: (x, y)
Let's say the distance between the two blue data points is 0.01 and the between any two red ones is 0.011. The matrix profile detect the two blue data points as the motif, but in my opinion, the 5 red ones are motifs and those two data points can be considered as outliers. Although I might have exaggerated here, similar cases might appear in some applications.
I appreciate any input regarding this idea.
I think it might be a good idea to come up with a method to relax the Matrix Profile. (I have been thinking about this idea for a while. I haven't got any conclusion yet. I am still thinking about it and I thought it might be a good idea to share it.
By the term "relax", I mean to consider close neighbors and not just closest data point. For instance, let's say we have seven data points where each data point is a Time Series of length two as: (x, y)
Let's say the distance between the two blue data points is 0.01 and the between any two red ones is 0.011. The matrix profile detect the two blue data points as the motif, but in my opinion, the 5 red ones are motifs and those two data points can be considered as outliers. Although I might have exaggerated here, similar cases might appear in some applications.
I appreciate any input regarding this idea.