How can k-means be applied here?

Hi,

Let me share my problem

I have few rectangular shapes boxes with specific height and width. Now, I have to cluster them so that the similar size boxes could be in one cluster and different size boxes shall be in another cluster. Now, if the longer side of a rectangle ( width or height) or the area s widely varies then boxes shall be dissimilar.

suppose I have a box with dimension ( 4*1) (width * height) and another box (1*4) (width * height), now both of them have same area but they have to be in different cluster. Now, if I am given a set of rectangle with (width * height) how can I apply k-means to them to clusterize, there are my doubts?

any approach from where I can start ?

regards

Answer 1

[Image Analyst]

I don't think kmeans can work with your boxes. Plus even if you manually scan your scatterplot looking for max values in your box, so that you can determine it's location, it depends on the order you use your boxes, like whether you do three 4*1 first then two 1*4 or vice versa.

If you have a lot of scatterpoints, you can turn it into an image and use quad tree decomposition, qtdecomp() in the Image Processing Toolbox:

[joy]

Thanks for your answer.

Actually, the problem can be viewed as if the width and height of rectangles are given then how would you classify or cluster those rectangles in different groups

[Image Analyst]

Please give some pictures or code to illustrate what you are dealing with. What are the two aces of your scatterplot? The width and height of a rectangle?

[joy]

along x axis I can plot the ratio of (shorter side/longer side) of all given rectangles, in y axis I can plot the area of all given rectangles, then the generated scatterplot can be used for clustering?

any views on this? is this could be an approach?

[Image Analyst]

I don't have the stats toolbox so I can't try kmeans. If you don't know the number of clusters, try one of the machine learning methods listed here: http://www.mathworks.com/machine-learning/index.html