Data Mining: Hash tree based support counting

Data Mining: Hash Tree based support counting

Hash tree is a very quick way to search an item. When there are many itemsets, hash tree could be used to find out if a given itemset has got required support count. But, how do we construct hash tree? The links I came across were very abstarct to define the hash tree implementation.

Suppose we want to insert (i.e. hash)
the following 3-itemsets into the tree
(9,3,6)
(8,7,1)

We have taken hashing function h(x) = N mod 3. This has three possible values for h(x) = {0, 1, 2}. Each value is a branch of a Hash tree node. So, each node will have three branches.

Now, lets insert Itemsets = {8, 7, 5} {9, 3, 6}

Start with I1 = {8, 7, 5}

Image

Remember, that we are considering 8 because it is lavel 1 of the tree. Next level, we will consider 7 and the next with 5.

The first item = 8
h(8) = 8 mod 3 = 2

Image

I2 = {9, 3, 6}
The first item = 9
h(9) = 9 mod 3 = 0

Image

Level 1
Now, the secons item of set I1 = 7
h(7) = 7 mod 3 = 1

Image

Now, the secons item of set I2 = 3
h(7) = 3 mod 3 = 0

Image

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2 thoughts on “Data Mining: Hash tree based support counting

  1. Lots of errors in your document, changing layout of the “slides” as well as constantly changing itemsets .. (8,7,1) then (8,7,5) and then even (8,7,6). The article needs to be properly restructured. It appears to me you didnt really know yourself how to demonstrate it for the audience..

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