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reformat.m
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reformat.m
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function [X,y] = reformat(nums,n,d,k, featureType, labelSize)
%% Reformat a sequence of numbers into training set and labels
%nums - randomly generated sequence of numbers
%n - number of inputs
%d - Number of preceeding values used for predictions
%k - Number of classes
%featureType - determines how features for each example are calculated:
% - 's': features are the 'd' preceding numbers
% - 'c': features are the counts of each of the k classes in the 'd'
% preceding numbers
%labelSize - the number of labels for each training example:
% - 1: label = class number
% - k: label is of size k with each entry representing one of the
% k classes. The corresponding class is marked with 1, rest are -1
%set default to sequence features and k labels
if (nargin < 6)
labelSize =k;
if(nargin <5)
featureType = 's';
end
end
X = zeros(n,d);
y = zeros(n,labelSize);
for i = 1:n
%Set Features depending on featureType
if(featureType == 's')
X(i,:) = nums(i:i+d-1);
else
if(featureType =='c')
seqI = nums(i:i+d-1);
for j = 1:k
X(i,j) = sum(seqI == j );
end
else
error('Unknown input for Feature type')
end
end
%Format labels depending on labelSize
if( labelSize == 1)
y(i) = nums(i+d);
else
if (labelSize == k)
for j = 1:k
if(nums(i+d) == j)
y(i,j) = 1;
else
y(i,j) = -1;
end
end
else
error('Unknown label size')
end
end
end
end