Probably this problem has occurred since the dataset is generating rules of 2-Itemsets. As because the datasets producing Rules of 1-Itemset is executing perfectly.
Please revert back, as to where should i making changes.
I am having a transaction dataset of 5 Rows and 1975 Columns. This ARMADA tool is not working for such a big dataset. When I am starting the tool for mining the Command window is showing :
Reading data file...
Counted LHS: 2 rules
And the execution is stopping. If this is the problem then how to form the Association rule mining for large dataset.
It is great code, but you need to fix your bugs: in order to achieve the same column for your both images, you can fix number of columns with the following codes:
nrows = max(size(I1,1), size(I2,1));
ncols = max(size(I1,2), size(I2,2));
nchannels = size(I1,3);
extendedI1 = [ I1, zeros(size(I1,1), ncols-size(I1,2), nchannels); ...
zeros(nrows-size(I1,1), ncols, nchannels)];
extendedI2 = [ I2, zeros(size(I2,1), ncols-size(I2,2), nchannels); ...
zeros(nrows-size(I2,1), ncols, nchannels)];
Also, Binary images don't give us the minimum numbers for Hausdorff Distance. I checked your codes with several binary images and all of the times the max Hausdorff Distance numbers were the correct answer, not the minimum number.
08 Feb 2014
Calculates the Hausdorff Distance between two sets of points in a Euclidean metric space.
I am having two vectors consisting of sequential locations visited by person-X and Y like:
X = [ (lat1,long1), (lat2,long2), (lat3,long3) ];
Y = [ (lat4,long4), (lat2,long2), (lat3,long3) ];
I need to find similarity between these two vectors. Can this Hausdorff distance help me in any way??