Hi, Robin. Thanks for your wonderfulreply ! it makes me understand this algrithms further.
But, i still have some questions. On Thu, Jul 29, 2010 at 6:37 AM, Robin Anil <[email protected]> wrote: > This is not regular FPGrowth. This has many other super improvements ;) > > 1) Its a faster method for mining of Top K patterns for each unique item: > How does it do it? First it makes the conditional tree for each feature in > I think the growth() function works in this way. > Bottom up manner(like the paper). Then it mines the conditional tree in top > and, the growthTopDown() function works as this manner( from top nodes to mining the frequent patterns, as you said, it will make the mining process fast). But i still can't understand why this function should use the growthBottomUp(). it seems that this growthBottomUp() function works like the growth() function from bottom node to top in the headerTable. growth() -> growthTopDown() -> growthBottomUp() Maybe, you just can help to explain how the growthBottomUp() works here. Thanks! down manner. This ensures it mines the top frequent sub patterns into a Heap > or in this case a PriorityQueue which allows me to remove the least > frequent > item easily. So everytime my queue is full and the support of the item in > the tree falls below that of the first entry in the Queue, I stop mining. > This makes it really really fast. Also I try to mine only the closed > patterns. See below: > If, > A,B,C => 4 > and > A, B => 4. > I select only the first as second is already part of first. > > > 2) The intermediate data which gets thrown in the map/reduces looks like an > FPTree called the Pattern tree. So I am able to compress more data making > the whole process faster > > 3). While making conditional trees, I try to zip them up and prune nodes > which fall below the min support. This is called FP-Bonsai algorithm. This > is blazing on tree which have a huge depth.(i.e the input data is having > longer transactions) > > > Hope this clears up your questions. Please take a look at the original > https://issues.apache.org/jira/browse/MAHOUT-157 issue. You will see how I > progressed from standard FPGrowth to this. Search mailing lists for older > discussions > > Robin > > On Tue, Jul 27, 2010 at 11:55 PM, Andrew Wang <[email protected] > >wrote: > > > Ye, thanks for your reply, Ted. > > > > As you know, after construct the FP-tree, we will use the growth fuction > to > > produce the frequent patterns. > > > > As the paper (Mining Frequent Patterns without Candidate Generation) > > described, we should get the patterns from the bottom of the > > HeaderTableAttributes (which always are leaf nodes in the pt-tree). > > > > So, maybe we just need to growthBottomUp() function. But, i also see > > growthTopDown() function in the FPGrowth.java. > > > > I just confused with this two functions, what are the differeces between > > them? > > > > Wish i describe my question clearly now. > > > > thanks > > > > On Wed, Jul 28, 2010 at 2:29 PM, Ted Dunning <[email protected]> > > wrote: > > > > > What is it that you don't understand about it? > > > > > > If you can give specific questions, you are much more likely to get a > > good > > > answer. The paper that you already have should give you most of the > > > general > > > hints that you need. From there, you should provide specific > questions. > > > > > > On Tue, Jul 27, 2010 at 10:13 PM, Andrew Wang < > > [email protected] > > > >wrote: > > > > > > > Now, only the growth(FPTree tree, MutableLong > minSupportMutable, > > > int > > > > k, FPTreeDepthCache treeCache, int level, int currentAttribute, > > > > StatusUpdater updater) function in the FPGrowth.jave cannot be > > understood > > > > by > > > > myself. > > > > > > > > Would you please tell how it works? or give me some papers to > > help > > > > me to understand it? thanks！ > > > > > > > > > > > > > > > -- > > http://anqiang1900.blog.163.com/ > > > -- http://anqiang1900.blog.163.com/
