GPTIPS 2, Symbolic Regression. Error

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Luis J Gilarranz
Luis J Gilarranz am 14 Feb. 2019
Hi,
I'm using GPTIPS 2 (https://sites.google.com/site/gptips4matlab/) to come up with a model that fits some data. The code runs, and I get the pareto front of models etc. However, I’m getting an error related to the symbolic toolbox.
For instance, when using “gpmodelreport(gp,84)” I get a screen print saying “Simplifying model ...” and then, an error
Error using gpmodel2sym (line 103)
Could not get symbolic object(s) for this model. Error using sym>convertChar (line 1459)
Character vectors and strings in the first argument can only specify a variable or number. To evaluate character vectors and strings representing symbolic expressions, use ‘str2sym’.
That error also shows up when I do “comparemodelsREC”, “gpmodel2sym”, “uniquegenes”...
Any idea?
Cheers!
LJ
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Luis J Gilarranz
Luis J Gilarranz am 15 Feb. 2019
I've narrowed down the error to the function gppretty.m, but substituting "sym" for "str2sym" doesn't solve the problem

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xox ir
xox ir am 18 Mär. 2019
Hello,
please create this function:
function y=xsym(x)
if isnumeric(x)
x=num2str(x);
end
y=str2sym(x);
Then add the code below:
if~verLessThan('matlab','9.3');sym=@xsym;end
At the begaining of gppretty.m
2019-03-18_102852.jpg
  1 Kommentar
Luis J Gilarranz
Luis J Gilarranz am 22 Mai 2019
Hi xox ir,
After following your instructions "gpmodelreport" works, however, when I want to use the gene browser to simplify the model I get the following error:
genes = uniquegenes(gp)
Scanning 100 models ...
Total encoded genes found: 373
Unique encoded genes found: 49
Decoding & simplifying genes...please wait.
Simplifying gene 1
Error using sym>convertChar (line 1459)
Character vectors and strings in the first
argument can only specify a variable or number. To
evaluate character vectors and strings
representing symbolic expressions, use 'str2sym'.
Error in sym>tomupad (line 1225)
S = convertChar(x);
Error in sym (line 214)
S.s = tomupad(x);
Error in uniquegenes (line 137)
symgenes{i} =
sym(genes.uniqueGenesDecoded{i});
Any idea?
Cheers,
LJ

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