Thanks Michael, I am not fluent in R but can hack my way through for sure! Really great to have this option. I had downloaded it, but did not realise it can evaluate too. Will definitely spin it up and explore functionality.
On Monday, 10 February 2020 14:53:06 UTC+11, Michael Duncan wrote: > > if you are familiar with R you can use the wrapper code i wrote for binary > classification problems: https://github.com/mjsduncan/Rmoses > > the documentation is crappy and it needs to be rewritten in the tidyverse > idiom but it handles producing and scoring combos on training and testing > partitions and producing feature counts from model ensembles. > > it includes a combo parser so you can try the combos on new samples. > > On Monday, February 10, 2020 at 5:30:19 AM UTC+8, linas wrote: >> >> >> >> On Sun, Feb 9, 2020 at 4:26 AM Lance White <[email protected]> wrote: >> >>> Hi to All, >>> >>> A really basic question about Moses. So I can run the examples and test >>> files no problems. But how do I use the output combo program? >>> >>> moses -H it -i disjunction.csv >>> >>> 0 or($1 $2 $3) >>> >>> -1 true >>> >>> -1 or($1 $2) >>> >>> >>> Let's say I want to use the following on a data set how do I feed it >>> values and get a result output by moses? >>> >>> >>> or($1 $2 $3) >>> >> >> Well, if you have three values, each being either true or false, well, >> just pipe those values through the logical or function, and you're done. >> >> Yes, this sounds silly, doesn't it? Every user of moses has built some >> large, complex system around it to feed it tables of data and then to >> process other data using these outputs. Unfortunately, all of these are >> proprietary systems, but it occurs to me that maybe one of these could be >> open-sourced. I'll have to ask. The one I know best can take structured and >> unstructured data from a variety of sources, filter and process these into >> training-data sets, collect up a number of best-fit moses colbo results, >> average them together into an ensemble, and then output that as a >> data-processing pipeline: you feed it tables (or individual lines from >> tables) and it makes predictions based on that input. Practical experience >> shows that it is more-or-less comparable to "decision forests" (a decision >> forest being an ensemble of decision trees; a decision tree being >> kind-of-like a combo program but obtained from different algorithms). Both >> moses and decision-forests max out at a certain level of accuracy, beyond >> with it takes an ungodly amount of training time to improve on. There was >> a nascent effort to apply deep learning techniques, but it foundered on a >> lack of funding. >> >> I'm not sure I answered your question, but that's what I've got. >> >> -- Linas >> >> -- >> cassette tapes - analog TV - film cameras - you >> > -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/61e93b57-44be-4976-bba8-82894f5a5ebc%40googlegroups.com.
