IRC logs of #shogun for Tuesday, 2011-08-02

--- Log opened Tue Aug 02 00:00:23 2011
alesis-novikblackburn, you there?01:22
blackburnalesis-novik: yes01:22
alesis-novikblackburn, what does the k argument in LLE mean?01:30
blackburnalesis-novik: the number of neighbors used for linear reconstruction01:31
alesis-novikthanks01:34
blackburnalesis-novik: why are you interested in lle? ;)01:35
alesis-novikI'm getting ready for my PhD and my supervisor asked me to do some stuff. Essentially I'm hitting stock profit data from multiple strategies as dimentions with different nldr techniques :D01:36
blackburnhmm let me know if you will get some success with it01:37
blackburnI'm pretty interested in manifold learning01:37
blackburnalesis-novik: how large is data?01:41
alesis-novikblackburn, huge, but I'm using subsets.01:42
blackburnand dimension?01:42
blackburnalesis-novik: I would suggest you to use LTSA first, it is faster >4x than LLE01:43
blackburnand sometimes it produces good results01:43
alesis-novikit has 161 dimensions01:43
blackburnI've applied LTSA to 200x200 images (40000d->2d)  and it was pretty well01:44
blackburnalesis-novik: http://dl.dropbox.com/u/10139213/shogun/LocalTangentSpaceAlignment%28k%3D40%29.png01:46
alesis-novikCool01:46
blackburnalesis-novik: the underlying dimension is angle and brightness or so01:46
blackburndimensions*01:46
alesis-novikthanks blackburn, this should be useful01:46
alesis-novikessentially I'm trying to find if there is some underlying structure that the strategies are using to get profit01:47
blackburnalesis-novik: are you using shogun techniques?01:47
blackburnalesis-novik: one 'advice' I would say - better use larger data than smaller, sometimes manifold is ruined with bad sampling01:48
alesis-novikblackburn, how many datapoints would be realistic with 161 dimensions?01:49
blackburnLTSA have something like O(N^2 + N*k^2) or so01:50
blackburnalesis-novik: it depends on sample size more than on data dimension, I guess time for 3k-5k examples will be under one minute01:51
alesis-novikI'm not worried that much about time, more about memory01:52
blackburnnow it uses NxN matrix01:52
blackburnin fact it should be sparse but we lack some sparse matrix routines..01:53
blackburnalesis-novik: >6k will take >2g memory01:54
alesis-novikcool01:54
alesis-novikone more thingy - any idea what could cause this in Classic MDS: RuntimeWarning: [WARN] Embedding is not consistent: features 3-4 are wrong01:55
blackburnalesis-novik: it is because eigenvalues are <001:55
alesis-novikah, ok. Thanks01:55
blackburnalesis-novik: just try to decrease target dimension, it means mds can't construct embedding to 4d space01:57
blackburnand usually number of positive eigenvalues shows the underlying dimension01:58
blackburne.g. for swissroll dataset it is 2 just as manifold dimension01:58
blackburnalesis-novik: you could use LandmarkMDS for large datasets with number of landmarks > dimensionality01:59
blackburnusually it is pretty accurate and much faster than Classic one02:00
alesis-novikI'll try that02:00
alesis-noviklandmarks > target or original dim?02:00
blackburnoriginal02:00
blackburnit uses triangulation like GPS use02:00
alesis-novikI don't really have experience with DR other than the linear ones :D02:00
blackburnas for me I don't have any experience with linear ones :D02:00
blackburnalesis-novik: landmark mds chooses some landmarks and constructs embedding as classic do for these landmarks02:01
blackburnfor other points it just compute triangulation02:02
alesis-novikthanks for the tips, this will be useful02:04
blackburnalesis-novik: I just tried to embed 7000 examples with landmark mds and it took 3.03s02:05
blackburnnot very useful but fast02:05
blackburnalesis-novik: and btw, laplacian eigenmaps will be implemented soon02:07
serialhexyou and your floating face images blackburn!!!02:57
blackburnserialhex: hehe02:58
serialhexi just looked at the image you posted a bit ago... and almost all of your images are like that :P02:59
serialhexso how have you been?02:59
blackburnwell that's how I can compare different methods ;)02:59
blackburnfine, but I don't understand why I'm not sleeping hehe02:59
serialhexyeah, it's like 9pm here, i can imagine how late it is there :P03:01
blackburn5am hehe03:02
serialhexoh man!03:02
serialhexyeah, i'm thinking of getting up extra early so i can talk to soeren & settle some Q's i had about how the configure stuff works03:02
blackburnboom03:07
CIA-87shogun: Sergey Lisitsyn master * ra2be4dd / (4 files): Added fast neighbor search for LLE, HLLE, LTSA with Fibonacci heap - https://github.com/shogun-toolbox/shogun/commit/a2be4dde5f464aa0e202e3d5ef1abb68209a09d503:07
serialhexso what? you have write access to the repo or somethin blackburn?03:09
serialhexand whats a fibonacci heap??03:09
serialhexsounds like it has something to do with the fib seq03:10
blackburnserialhex: yes I have, since june or so ;)03:12
serialhexcool cool03:12
blackburnserialhex: fibonacci heap is a data structure like binomial heap03:12
blackburnindeed, it is related to fib seq03:13
serialhexcool03:14
blackburnit is good for dijkstra algo03:14
blackburnbecause extract-min have O(lg n) time complexity03:14
serialhexnice03:14
blackburnactually it can't be faster hehe03:15
blackburnbecause the fastest sort is O(n log n)03:15
serialhexunfortunatey i only know enough to know that i don't know enough :P  i need to learn more!03:15
serialhexniiice!!03:15
* serialhex is reading the wikipedia article, and should have done that in the first place :P03:17
blackburnI just heard us senate got some convention, right?03:18
serialhexyeah, something like that... i should really pay more attention but i don't really03:18
blackburnI pay attention to it because usd/rub rate depends on that03:18
blackburnand I want higher rate hehe03:19
@bettyboohe03:19
serialhexyeah, our $$ is going down unfortunately... because our polittons are all crooks!03:19
serialhexthat's a big reason why i dont pay much attention: it's too depressing!!03:20
blackburnhaha what would you say if you was in russia03:22
serialhexi don't know, but probably about the same :D  they're all crooks, wherever they are in the world!03:23
blackburnat least yours obey laws :)03:23
blackburn5-25 am and somebody is jumping, the whole house is joggling :D03:25
blackburnuh I have to sleep03:49
blackburnserialhex: see ya03:49
serialhexnite blackburn03:49
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heikosonney2k, around?12:36
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@sonney2kheiko, today only at >20hrs14:49
heikosonney2k, ok14:49
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sploving1sonney2k, are you around?16:19
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CIA-87shogun: Soeren Sonnenburg master * r6387718 / (29 files in 9 dirs):21:05
CIA-87shogun: Merge pull request #258 from karlnapf/master21:05
CIA-87shogun: model selection now really works on model_selection_parameters (+24 more commits...) - https://github.com/shogun-toolbox/shogun/commit/6387718cb3a8b19bb0ff3ff603cfefd0714056db21:05
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blackburnsonney2k: around?21:44
@sonney2ky21:44
@sonney2kblackburn, you too ;-)21:46
@sonney2k?21:46
blackburnwhat me? ;)21:46
@sonney2karound?21:46
blackburnsonney2k: sagen sie mal, have you ever worked with mutual k-nearest neighbor graphs?21:46
@sonney2kblackburn, nitschewo net21:46
blackburnsonney2k: ploho21:47
blackburnsonney2k: so, howdy?21:47
@sonney2kI finished plumbing my 'server' back together21:48
@sonney2know it is time to do some buildbot stuff ... I really hope I have that going by the end of the week21:48
blackburnhow do you mind we can use it?21:49
@sonney2kblackburn, I could install buildbot - then we get nice pictures like this http://trac.buildbot.net/wiki/ScreenShots21:51
blackburnsonney2k: so every change will be checked one more time on buildbot and we will fast notice if something goes bad?21:52
@sonney2kblackburn, or detect a bug in the buildbot yes :)21:53
blackburnI see21:53
blackburnit is pre-release thing, right?21:53
blackburnsonney2k: ah! and you plan to do some VM so we can check compilation under windoze/osx, right?21:54
blackburnor not?21:54
@sonney2kblackburn, it is a debian package for some time21:54
@sonney2kblackburn, if I manage osx and some cygwin too21:54
@sonney2kblackburn, then I put sth like this on my desk http://mackeblog.blogspot.com/search/label/lavalamp21:55
blackburnahaha21:56
blackburnyou will wake up not only with baby's cry but with shogun's cry too21:56
blackburnand robovoice should say ZZZZZZZ COMPILATION FAILED21:56
@sonney2kblackburn, I actually have an alarm light in my office22:01
@sonney2kwould be pretty impressive to use it for that task :D22:01
blackburnfire alarm, terrorist alarm, shogun alarm22:02
@sonney2knahh shogun alarm should be rank #122:02
blackburnsonney2k: how expensive to use DynArray for storing integers?22:03
@sonney2kit is like int[]22:03
@sonney2kno error checks..22:03
blackburnhmm why is it Dyn?22:03
blackburnhmm I need a Set22:04
blackburnsonney2k: we don't have Set, right22:04
blackburn?22:04
@sonney2kblackburn, we have a poor mans set22:05
@sonney2kCSet22:05
blackburnhow poor it is?22:05
@sonney2kit is a Q&D hack with O(n) insert/dedup costs22:05
@sonney2kI wrote this only for the memory tracing stuff22:06
blackburnah I see22:06
@sonney2kblackburn, so sth great for gsomix I would say :)22:06
@sonney2kHe seems to be data structures affine22:06
blackburnI've suggested him to parallelize distance and kernels22:06
blackburnsonney2k: can I use std for now?22:07
@sonney2kwell if you have too....22:08
blackburnsonney2k: we already have some std in mkl or so22:08
blackburnsonney2k: why are you against it btw?22:08
@sonney2kI am not a big fan of using C++ libraries for standard tasks... I guess nowadays historical esoteric reasons :-|22:11
blackburnwell I don't like std-like code with iterators, much templates and blablabla22:12
blackburnbut the set is example where we are going to duplicate efforts or so22:12
blackburnsonney2k: is it ok to just make a front-end to std:set?22:14
@sonney2kblackburn, yeah but where do you draw the line? How good is the 'set' implementation in std? What overhead does it involve?22:14
blackburnI guess it should be very good22:14
blackburnhm stl not std22:15
@sonney2kblackburn, I had the issue that using qsort() from c library was 10 times slower than my stupid qsort() and it was ruining a whole algorithm because suddenly we had an unexpected bottleneck22:18
blackburnuh22:18
@sonney2kso I am saying check carefully ...22:18
blackburnsonney2k: btw fibonacci heap makes possible to do kNN finding in O(klg n), I've already adapted my LLE* algos to do that faster22:20
@sonney2knice... does john langford's covertree improve this further?22:20
blackburnyes, sure22:21
blackburnfor large dimensions22:21
blackburnbut in fact it is not a bottleneck22:21
blackburnspectral methods involve large-scale eigenvalues problems and it is the most time-demanding thing22:22
blackburnso covertree will improve only kNN22:23
@sonney2kblackburn, or we use that here22:25
@sonney2khttp://bitten.edgewall.org/build/trunk22:25
@sonney2k'bitten'22:25
@sonney2knahh buildbot looks better...22:26
@sonney2kblackburn, buildbot seems to even have an IRC bot :)22:30
blackburnhehe22:30
@sonney2kso this channel will finally be taken over by robots :D22:30
@bettyboorotfl22:30
blackburnit's funny to watch bettyboo and buildyboo will have a conversation22:32
@bettybooblackburn: oh, those 14 billions... i don't watch much news so i dont *know* but tyhere are soem people taking it sereously, and others probably aren't22:32
--- Log closed Wed Aug 03 00:00:34 2011

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