verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
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< msohcw> Hi. This might be a little (or very) late but I was wondering if you guys think you might still be looking for someone to work on the RL project for GSoC.
< msohcw> A little short intro about myself, I got interested in ML at the end of 2015/beginning of 2016, particularly interested in deep RL. I implemented the deepmind papers from scratch (to play flappy bird!) specifically, DQN, DDQN, prioritised experience replay and deep-duelling Q networks.
< msohcw> I'm also familiar with current state of the art like A3C, DDPG etc.
< msohcw> I'm currently with Machine Learning @ Berkeley, a student organisation that focuses on machine learning projects, and I'm on a team working on a deep RL library right now.
< msohcw> I'm fluent with C++, albeit maybe not to the extent that you guys require, but I'm definitely willing to pick it up.
< msohcw> Oh and if it's a bonus, I've also worked on OpenAI problems, and I think you guys are interested in integrating those in?
< msohcw> I've read through most of the ML-related GSoC projects and mlpack has the most interesting one by far. Is the RL project going to be a focus for the team? Are there any particular areas which you are looking specifically for?
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< nish21> rcurtin: I have shared my draft proposal. Could you take a look when you are free?
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< nish21> looking forward for any helpful and valuable comments
< nish21> thanks :)
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< jarvis_> zoq: I have incorporated your suggestions. Please have a look when you have the time.
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< cannon4> Getting the following errors while running "cmake ../" in my terminal:
< cannon4> CMake Error at CMake/FindArmadillo.cmake:326 (message):
< cannon4> ARMADILLO_INCLUDE_DIR-NOTFOUND/armadillo_bits/config.hpp not found! Cannot
< cannon4> determine what to link against.
< cannon4> Call Stack (most recent call first):
< cannon4> CMakeLists.txt:189 (find_package)
< cannon4> -- Configuring incomplete, errors occurred!
< cannon4> CMake Error at CMake/FindArmadillo.cmake:326 (message):
< cannon4> ARMADILLO_INCLUDE_DIR-NOTFOUND/armadillo_bits/config.hpp not found! Cannot
< cannon4> determine what to link against.
< cannon4> Call Stack (most recent call first):
< cannon4> CMakeLists.txt:189 (find_package)
< cannon4> -- Configuring incomplete, errors occurred!
< cannon4> Haven't been able to figure this out for quite some time now.
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< zoq> cannon4: Hello, do you have Armadillo installed?
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< cannon4> zoq: Yes
< cannon4> Oh, it's done. Thank you!
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< naxalpha> zoq: This is package without redist but it doesn't work https://www.nuget.org/packages/mlpack-windows/2.2.0.4
< cult-> hi
< cult-> what boosting algorithms are present in the library?
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< cult-> i still need a better jump model
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< nish21> cult: mlpack has adaboost
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< travis-ci> mlpack/mlpack#2223 (master - bd7f327 : Ryan Curtin): The build passed.
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< whosc> Hello, How do you know iff a system can be solved using linear or non linear ways?
< Trion> If data can be represented as a line or can be separated by a line then use linear ways otherwise non-linear ways
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< mich> hello
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< zoq> mich: Hello there!
< Trion> :P Thanks for the comments zoq! The Agent finally worked!
< zoq> Trion: No problem, let me know if you have any further questions.
< Trion> zoq: :P I still broke something, the iex server we have is giving "No module named monitoring" even though I installed it and verified in python REPL. I am connecting to it via 127.0.0.1:4040
< whosc> Trion, and how do i know if the data can be separated by a line?
< whosc> The basic problem is one that can be solved by parameterization.. I have an object , i just need to keep watch on real time data to make sure environmental variables do not cross a certain threshold.
< whosc> Its a yes or a no type. Like the object is safe, or the object is unsafe.
< Trion> I mostly set up a data visualization using matplotlib in python, makes understanding data easier
< zoq> Trion: Sounds like you use an old version of gym, in the newer versions "env = wrappers.Monitor(env, directory)" isn't used anymore in favor of nv = wrappers.Monitor(env, directory). If you use the git version: https://github.com/openai/gym#installation you should be fine.
< zoq> line 129 and 16
< zoq> I have to step out for a while, back later.
< Trion> whosc: You can train Naive Bayes Classifier with labeled data for that object if the object is safe or unsafe
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< vivekp> rcurtin: Regarding the SMORMS3 PR, I don't understand how we'd use for_each() and a lambda to avoid allocating an extra matrix, stepSizeMat
< vivekp> Could you elaborate a bit?
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< rcurtin> vivekp: I am in meetings all day today but I can probably find a chance to write something on.that PR, don't worry :)
< rcurtin> I'll comment when I have a chance
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< vivekp> rcurtin: ah, okay thanks :)
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< ironstark> Can we add benchmark scripts for graphlab create library in python?
< rcurtin> ironstark: sure, as long as graphlab create is free, I can install it on the benchmarking systems
< ironstark> for that we need to update the dataset folder and add some .gl files because the library requires .gl extension datasets
< rcurtin> could you write a shim that takes in .csv and outputs .gl?
< rcurtin> the datasets are pretty big so it would be good to try and keep the size from exploding
< rcurtin> so making a local copy would be preferable to adding lots to the repos
< ironstark> I can try
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< ironstark> I'll first see whether there are options to directly read datasets in csv format or not
< rcurtin> sure, I would imagine that there are
< rcurtin> I remember working with graphlab from years ago and I seem to remember using CSVs
< rcurtin> are they still developing Create or have they kind of disappeared since being bought by Apple?
< ironstark> It is still being developed I guess but its not open source
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< ironstark> also to install graphlab for free we need to register as an academic user
< ironstark> Is it possible for mlpack to register as an academic user?
< chittaranjan> Are we inclined towards benchmarking more libraries, or more algorithms of libraries we have now?
< rcurtin> ironstark: honestly if they aren't giving it away for free and we have to register, it's going to be a lot of maintenance to keep it installed and working, and I think it's not worth bothering
< rcurtin> unless they come to us and contribute some patches to the benchmarking system or something, which I doubt they will
< rcurtin> chittaranjan: either is fine
< ironstark> rcurtin : ya it requires registration and regular product key renewals to maintain so I should drop this idea for now
< rcurtin> agreed
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< zoq> ironstark: If you search for other interesting libraries, I guess https://github.com/teemupitkanen/mrpt might be interesting to look into, would be interesting to see if mlpack can compete.
< ironstark> zoq: Thanks I'll look into this one and try to implement
< zoq> Maybe rcurtin already tested the method ... not sure
< ironstark> Also I have removed the if condition in the randomforesttest PR(#34). Please test it once.
< zoq> ironstark: I did, and it looks good.
< ironstark> okay thanks a lot :)
< rcurtin> the dimensionality in all their comparisons is very high (for mrpt), I would be interested to see how it does on lower-dimensional datasets
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< ironstark> okay is iris dataset a good example for lower-dimensional dataset?
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< rcurtin> ironstark: iris is really small, but it is low dimensional
< rcurtin> the existing dataset we are already using for the kNN benchmarks should be ok
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< ironstark> okay
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