It's a trivial question. The reason is that it is not a issue that is central to AGI. The problem of relative relations between observations, which are conceptually complex, cannot be defined well as a relation between two numbers. True, relations between two numbers can be conceptually complex but that potential is different than the potential for complexity of something like observations. The only inference that I can make is that you are, knowingly or unknowingly, asking someone if they have a solution for embedding general conceptual complexity into a relation between two numbers. If that is what you are asking then the question is not being phrased well.
I do notice that although my criticism includes a reason that supports it, the reason is not phrased too well. You have to have some idea what I am getting at in order to understand what I am getting at. And, that inadequacy of explanation probably does represent an inadequacy of literal formalization of the problem. In other words, I don't even know what the fundamental issues of the abstraction of the problem are even though I am quite aware of it. So in a way, my criticism is as trivial as MM's question. But, one might suppose that the study of a research problem is not going to end with a perfect understanding but an understanding that is adequate for some purpose, especially when a technological problem is being considered. From that point of view, my criticism takes this a step further. And even if you already were aware of what I was saying (even before I said it), then my criticism still takes the discussion a step back to a central problem of AGI in our time. Jim Bromer Jim Bromer On Thu, Feb 20, 2014 at 12:01 AM, Piaget Modeler <[email protected]>wrote: > Hi all, > > For all you statisticians out there... > > I'm working on an algorithm for numeric similarity and would like to > crowdsource the solution. > > Given two numbers, i.e., two observations, how can I get a score between > -1 and 1 indicating their proximity. > > I think I need to compute a few things, > > 1. Compute the *mean* of the observations. > 2. Compute the standard deviation *sigma* of the observations. > 3. Compute the *z-score* of each number. > > Once I know the z-score for each number I knew where each number lies > along the normal distribution. > > After that I'm a little lost. > > Is there a notion of difference or sameness after that. > > This might help.. > > > http://www.dkv.columbia.edu/demo/medical_errors_reporting/site010708/module3/0510-similar-numeric.html > > Your thoughts are appreciated ? > > Michael Miller. > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/24379807-f5817f28> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
