Too many input arguments

Hello,

Can somebody explain to me why when I run the code I get this message.

Error using aresparams

Too many input arguments.

Error in test (line 17)

trainParams = aresparams('maxFuncs', -1, 'c', 3, 'cubic', true, 'cubicFastLevel', 2,'selfInteractions',1, 'maxInteractions', 1, 'threshold',1e-4,'prune',

true, 'fastK',20, 'fastBeta',1, 'fastH',5,'useMinSpan', -1,'useEndSpan',-1, 'maxFinalFuncs',inf, 'endSpanAdjust',1, 'newVarPenalty',0.1,'terminateWhenInfGCV',false, 'allowLinear',0);

[Dyuman Joshi]

There is no built-in or toolbox function named as aresparams in MATLAB.

Seems like it's a user-defined function.

Please copy and paste the output of this code -

which -all aresparams

[Image Analyst]

It's not a built-in MATLAB function. Check the documentation for it.

help aresparams

--- aresparams not found. Showing help for parseparams instead. ---

 PARSEPARAMS Finds first string argument.
    [REG, PROP]=PARSEPARAMS(ARGS) takes cell array ARGS and
    separates it into two argument sets:
       REG being all arguments up to, but excluding, the
    first string argument encountered in ARGS.
       PROP contains all other arguments after, and including,
    the first string argument encountered.
 
    PARSEPARAMS is intended to isolate possible property
    value pairs in functions using VARARGIN as the input
    argument.

Answer 1

[Voss]

According to section 2.2 (page 7) of the attached pdf document, aresparams should be called like:

trainParams = aresparams(maxFuncs, c, cubic, cubicFastLevel, ...
    selfInteractions, maxInteractions, threshold, prune, fastK, fastBeta, fastH, ...
    useMinSpan, useEndSpan, maxFinalFuncs, endSpanAdjust, newVarPenalty, ...
    terminateWhenInfGCV, yesInteract, noInteract, allowLinear, forceLinear)

Which means that you don't pass the parameter names ('maxFuncs','c','cubic', etc.), only their values (-1,3,true, etc.).

So instead of this:

trainParams = aresparams('maxFuncs', -1, 'c', 3, 'cubic', true, 'cubicFastLevel', 2, ...
    'selfInteractions',1, 'maxInteractions', 1, 'threshold',1e-4,'prune',true, 'fastK',20, ...
    'fastBeta',1, 'fastH',5,'useMinSpan', -1,'useEndSpan',-1, 'maxFinalFuncs',inf, ...
    'endSpanAdjust',1, 'newVarPenalty',0.1,'terminateWhenInfGCV',false, 'allowLinear',0);

Do this:

trainParams = aresparams(-1, 3, true, 2, 1, 1, 1e-4, true, 20, 1, 5, -1, -1, inf, 1, 0.1, false, 0);