genetic algorithm for feature selection

Hi

I used the code in MathWorks and I edited but I couldn't get the result I find these error after i run the code

    Not enough input arguments.

Error in lastga>fitnessfunction (line 47)
fitnessRMSE = sqrt(sum(bsxfun(@minus,X,Y').^2,2)/20);

Error in createAnonymousFcn>@(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = @(x) fcn(x,FcnArgs{:});

Error in makeState (line 47)
            firstMemberScore = FitnessFcn(state.Population(initScoreProvided+1,:));

Error in gaunc (line 40)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);

Error in ga (line 356)
            [x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...

Error in lastga (line 23)
[chromosome,~,~,~,~,~] = ga(FitnessFcn,nVars,options);

Caused by:
    Failure in initial user-supplied fitness function evaluation. GA cannot continue.

>>

I Use 2015b version . I used the code for genetic algorithm for feature selection for near infrared data

    Clear all
    Data  = load('data.mat')
    % This is available in Mathworks
    GenomeLength =401; % This is the number of features in the dataset

    options = gaoptimset('CreationFcn', {@PopFunction},...
                         'PopulationSize',50,...
                         'Generations',100,...
                         'PopulationType', 'bitstring',... 
                         'SelectionFcn',{@selectionroulette},...
                         'MutationFcn',{@mutationuniform, 0.1},...
                         'CrossoverFcn', {@crossoverarithmetic,0.8},...
                         'EliteCount',2,...
                         'StallGenLimit',100,...
                         'PlotFcns',{@gaplotbestf},...  
                         'Display', 'iter'); 
    rand('seed',1)
    nVars = 20; % 
    FitnessFcn = @fitnessfunction ; 
    [chromosome,~,~,~,~,~] = ga(FitnessFcn,nVars,options);
    Best_chromosome = chromosome; % Best Chromosome
    Feat_Index = find(Best_chromosome==1); % Index of Chromosome
    end

    %%%POPULATION FUNCTION
    function [pop] = PopFunction(GenomeLength,~,options)
    RD = rand;  
    pop = (rand(options.PopulationSize, GenomeLength)> RD); % Initial Population
    end

    %%%FITNESS FUNCTION   You may design your own fitness function here
    function [fitnessRMSE] = fitnessfunction(X ,Y)
    X= data.x ;
    Y=data.y ;
    fitnessRMSE = sqrt(sum(bsxfun(@minus,X,Y').^2,2)/nvar);
    end

[Walter Roberson]

Please post the complete error message, everything in red.

(We do not have your data.mat file so we cannot just run the code ourselves to test.)

[Dheeb Albashish]

nVars = 20; %

should be 401 as number of features.

function [fitnessRMSE] = fitnessfunction(pop)