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I tried to test application on 10 dimensional points. But did not wait for the result. Dataset was very simple - only 3 points.
1;1;1;1;1;1;1;1;1;1
2;2;2;2;2;2;2;1;1;1
11;11;11;22;22;22;33;22;22;22
I found condition when it works. If value in one dimension is close to all other points - it works.
And i found also, the more dimnsions the less deviation is required for such behavior.
The text was updated successfully, but these errors were encountered:
valera7979
changed the title
Bad performance in N>5 dimensions
Infinite work if in dataset presents a point with a sharp deviation in all dimensions
Feb 5, 2018
I tried to test application on 10 dimensional points. But did not wait for the result. Dataset was very simple - only 3 points.
1;1;1;1;1;1;1;1;1;1
2;2;2;2;2;2;2;1;1;1
11;11;11;22;22;22;33;22;22;22
I found condition when it works. If value in one dimension is close to all other points - it works.
1;1;1;1;1;1;1;1;1;1
2;2;2;2;2;2;2;1;1;1
11;11;11;22;22;22;33;22;22;2 <--
And i found also, the more dimnsions the less deviation is required for such behavior.
The text was updated successfully, but these errors were encountered: