Wednesday, November 16, 2016

"End of Life" for a neural net

Because they are black boxes giving no window into the multi dimensional measurement space where "clusters" are forming during machine learning, you will never see just how non-convex the classification regions are - how topologically different they are from the original regions in object space. Un-justified assumptions of convexity and a blind belief in the applicability of a random Euclidean metric have created a situation where, inevitably, a sample will get added from "category A" that is closer the known examples from "category B". From there, it is only a matter of time when the two categories start merging and the system deliver more and more incorrect classifications.
It seems to me this is almost inevitable.
At first a neural net system seems great. A small number of examples have been added to the system and they are far enough apart to work as nearest-neighbor classifiers. But then we start adding other examples for greater "accuracy". From personal experience, two things are happening now. Counter examples are starting to show up and so they are added as new training examples. Also the developer is beginning to be hypnotized (PRADHS - "pattern recognition algorithm developers hypnosis syndrome") into believing objects belong in the category, if their system tells them that is where the object belongs. This leads to the addition of more and more boundary case examples. Rather than becoming more accurate, the system has actually become useless and incapable of delivering accuracy greater than a not-very-good level like 65%. That is machine learning "end of life".

I believe that Google may have reached end of life in its search algorithm. You can always find straw in a haystack but I am afraid that you can no longer find a needle there. As far as I am concerned, when I search for "Barbara Waksman" and they return pages with both words but not all pages where the words are adjacent, then what I am seeing is a whole lot of false positives. The world seems much too accepting of these Google errors. When Netflix makes the same error it is SO bad that I can utilize their bogus search results as a backdoor search for random movie titles that are not available otherwise - a different Netflix error. 

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