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Hello John and Hello to everyone
What if the human intuition and vision is too specific to cognize patterns in data, what if we used machine vision to identify 'keypoints' as features in temperature data (per day) and then use machine learning to cluster these keypoints (derivatives taken on the splined original data no normalization):
Paul check out the Himalayas.
Mahler patterns are visible, so they are not artifacts of normalization.
In particular SURF keypoints, does not have to be SURF or SIFT we could choose any or make our own: