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] > <javascript:>> 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/d2a118d3-06b2-464a-a2fc-a903daf26b46%40googlegroups.com.
