R squared tells you the percentage of the variance of a variable predictable by another.
--- Frank C. Wimberly 140 Calle Ojo Feliz, Santa Fe, NM 87505 505 670-9918 Santa Fe, NM On Mon, Nov 29, 2021, 12:23 PM <[email protected]> wrote: > I agree. I use the distinction (artificial vs natural) as a rhetorical > crutch. What we *should* do, what I've asked Nick to do, is talk about how > we *measure* outcomes, how they *scale*. If we run something like a > principal component analysis on all the outcomes and let the data tell us > which parts are primary and which parts secondary, then we don't need the > artifical vs natural distinction (or the epi- vs phenomena distinction) at > all. This outcome's salience is 0.00001, that outcome's salience is 10000.0. > > > > This is the kind of work that Frank has done. We will hear from him > momentarily, I assume. As I understand it, such work can rank the efficacy > of a cause for each of its effects. But it does not tell you to care only > about the most effected effects. That is something you are doing. That’s > your frame. My frame, as a development/evolutionist blah blah tells me to > privilege effects that feed back on causes because these are the only kinds > of effects that in time can shape the development of a biological of > technological artifact. So loopy effects are “primary” to me. Perhaps I > should use your word “salient”, in this case. Yes, I think that would be > better. > > > > N > > Nick Thompson > > [email protected] > > https://wordpress.clarku.edu/nthompson/ > > > > -----Original Message----- > From: Friam <[email protected]> On Behalf Of u?l? ?>$ > Sent: Monday, November 29, 2021 11:19 AM > To: [email protected] > Subject: Re: [FRIAM] The epiphenomenality relation > > > > I agree. I use the distinction (artificial vs natural) as a rhetorical > crutch. What we *should* do, what I've asked Nick to do, is talk about how > we *measure* outcomes, how they *scale*. If we run something like a > principal component analysis on all the outcomes and let the data tell us > which parts are primary and which parts secondary, then we don't need the > artifical vs natural distinction (or the epi- vs phenomena distinction) at > all. This outcome's salience is 0.00001, that outcome's salience is > 10000.0. > > > > Of course, if you change the measure, you get a different distribution. > But if we don't talk, at all, about the measure(s) being used for the > classification, then we're just talking nonsense. > > > > I don't like the following words. But the distinction between > [un]supervised learning is similar. Except there, I tend to argue that > there is no such thing as unsupervised learning. The very choice of any > family of models biases the eventual model you select. > > > > On 11/29/21 9:10 AM, Marcus Daniels wrote: > > > I'm not clear on where/why one draws the line between artificial and > natural. Artificial things have resulted from natural processes. These > higher-order and relatively sharp fitness landscapes have mesas we call > features. They usually don't involve people dying or failing to > reproduce, but they do involve organized behavior by humans stopping, e.g. > companies that go bankrupt. A continuous integration system running > regression tests seems to have some properties of selection. > > > > > > -----Original Message----- > > > From: Friam <[email protected]> On Behalf Of ? glen > > > Sent: Monday, November 29, 2021 6:14 AM > > > To: The Friday Morning Applied Complexity Coffee Group < > [email protected]> > > > Subject: Re: [FRIAM] The epiphenomenality relation > > > > > > Right. Agnostic discovery of the artifacts resulting from an artificial > machine comes much closer to what happens in natural systems, yes. Those > artifacts would only be considered secondary or side-effects IF the > exploration were NOT agnostic, motivated. You can only separate the > artifacts into primary vs secondary IF you had a purpose in the assembly. > No purpose, no distinction of primary vs secondary. > > > > > > But what you can do is measure the impact of all the resulting > artifacts, on some scale, and order them that way, a distribution of > primacy. Outcome O1 might be Y times more impactful, downstream than > outcome O2. If THAT were what we meant by "secondary" effect, then it would > be less laden with intention. > > > > > > But that's not what Nick seems to be doing. By insisting that some > effects are, by definition, secondary and others primary, he's asserting an > intention/purpose to the assembly. > > > > > > > > > On November 28, 2021 9:40:42 PM PST, Marcus Daniels < > [email protected]> wrote: > > >> An ab initio simulation of a biochemical system would have a foundation > of some human-engineered code and the atomic model simulated might have > some simplifying assumptions. The low energy configurations and dynamics > are discovered, not engineered. Yet it is all reproducible on a digital > computer with precise causality and in some cases has shown fidelity with > physical experiments. > > >> > > >>> On Nov 28, 2021, at 9:14 PM, ⛧ glen <[email protected]> wrote: > > >>> > > >>> This sounds like impredicativity, which can be a problem in parallel > computation (resulting in deadlock or race). Unimplemented math has no > problem with it, though. And I'm guessing that some of the higher order > proof assistants find ways around it. A definitional loop seems distinct > from iteration. So, no; I don't see a problem with iteration in digital > computation. I simply don't think the intelligent design we do when > programming is analogous to biological evolution. The former clearly has > side effects (epiphenomena). I argue the latter does not. > > >>> > > >>>> On November 28, 2021 5:40:31 PM PST, Marcus Daniels < > [email protected]> wrote: > > >>>> Glen had said something a while ago implying that (that trivial > meaning for) loops were somehow more challenging for digital computers. > I didn’t get it. > > >>>> > > > > -- > > "Better to be slapped with the truth than kissed with a lie." > > ☤>$ uǝlƃ > > > > > > .-- .- -. - / .- -.-. - .. --- -. ..--.. / -.-. --- -. .--- ..- --. .- - . > > FRIAM Applied Complexity Group listserv > > Zoom Fridays 9:30a-12p Mtn UTC-6 bit.ly/virtualfriam > > un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com > > FRIAM-COMIC http://friam-comic.blogspot.com/ > > archives: > > 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ > > 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ > > .-- .- -. - / .- -.-. - .. --- -. ..--.. / -.-. --- -. .--- ..- --. .- - . > FRIAM Applied Complexity Group listserv > Zoom Fridays 9:30a-12p Mtn UTC-6 bit.ly/virtualfriam > un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com > FRIAM-COMIC http://friam-comic.blogspot.com/ > archives: > 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ > 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ >
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