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hackassin
GitHub Repository: hackassin/Coursera-Machine-Learning
 Path: blob/master/Week 9/Programming Assignment - 8/ex8/submit.m
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function submit()

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  addpath('./lib');

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  conf.assignmentSlug = 'anomaly-detection-and-recommender-systems';

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  conf.itemName = 'Anomaly Detection and Recommender Systems';

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  conf.partArrays = { ...

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    { ...

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      '1', ...

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      { 'estimateGaussian.m' }, ...

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      'Estimate Gaussian Parameters', ...

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    }, ...

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    { ...

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      '2', ...

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      { 'selectThreshold.m' }, ...

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      'Select Threshold', ...

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    }, ...

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    { ...

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      '3', ...

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      { 'cofiCostFunc.m' }, ...

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      'Collaborative Filtering Cost', ...

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    }, ...

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    { ...

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      '4', ...

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      { 'cofiCostFunc.m' }, ...

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      'Collaborative Filtering Gradient', ...

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    }, ...

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    { ...

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      '5', ...

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      { 'cofiCostFunc.m' }, ...

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      'Regularized Cost', ...

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    }, ...

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    { ...

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      '6', ...

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      { 'cofiCostFunc.m' }, ...

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      'Regularized Gradient', ...

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    }, ...

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  };

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  conf.output = @output;

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  submitWithConfiguration(conf);

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end

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function out = output(partId, auxstring)

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  % Random Test Cases

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  n_u = 3; n_m = 4; n = 5;

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  X = reshape(sin(1:n_m*n), n_m, n);

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  Theta = reshape(cos(1:n_u*n), n_u, n);

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  Y = reshape(sin(1:2:2*n_m*n_u), n_m, n_u);

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  R = Y > 0.5;

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  pval = [abs(Y(:)) ; 0.001; 1];

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  Y = (Y .* double(R));  % set 'Y' values to 0 for movies not reviewed

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  yval = [R(:) ; 1; 0];

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  params = [X(:); Theta(:)];

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  if partId == '1'

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    [mu sigma2] = estimateGaussian(X);

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    out = sprintf('%0.5f ', [mu(:); sigma2(:)]);

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  elseif partId == '2'

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    [bestEpsilon bestF1] = selectThreshold(yval, pval);

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    out = sprintf('%0.5f ', [bestEpsilon(:); bestF1(:)]);

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  elseif partId == '3'

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    [J] = cofiCostFunc(params, Y, R, n_u, n_m, ...

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                       n, 0);

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    out = sprintf('%0.5f ', J(:));

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  elseif partId == '4'

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    [J, grad] = cofiCostFunc(params, Y, R, n_u, n_m, ...

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                             n, 0);

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    out = sprintf('%0.5f ', grad(:));

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  elseif partId == '5'

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    [J] = cofiCostFunc(params, Y, R, n_u, n_m, ...

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                       n, 1.5);

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    out = sprintf('%0.5f ', J(:));

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  elseif partId == '6'

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    [J, grad] = cofiCostFunc(params, Y, R, n_u, n_m, ...

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                             n, 1.5);

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    out = sprintf('%0.5f ', grad(:));

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  end 

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end

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