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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< pawsed>
Has mlpack touched any sort of NLP based machine algos yet?
< pawsed>
If not , can i start an issue on that?
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< ShikharJ>
pawsed: Hi, could you elaborate a bit on "NLP-based Machine Learning" Algorithms? Do you mean algorithms that have applications in NLP (Machine Translation and so on)?
< pawsed>
yeah basically rnn's and lstm's
< ShikharJ>
I think that these are present in methods/ann folder. You might want to take a look there.
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< aneeshj>
Hi all, is there an linux image with all the dependencies for mlalpack installed? I tried building from scratch but ran into verror building adaboost . The issue relating to this was closed due to inactivity
< aneeshj>
I can share a snapshot if anybody wants it
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< namrata_>
Hi, I was installing mlpack on Ubuntu and then was trying to run mlpack_knn example as given in the README file. However, I figured out that the file has either now been renamed or removed from the codebase. Please let me know if I'm right about this? Also, if I am right, should I go ahead and open an issue and send a PR for the same?
< namrata_>
I got a command not found error when running "mlpack_knn --help" as given in the README. However, I was able to run other example commands like "mlpack_allknn --help""
< zoq>
pawsed: There is currently no pipeline for NLP, however, the main functionality exists.
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< namrata_>
zoq: I installed it via apt-get and the version installed is 2.0.1.
< aneeshj>
namrata_: I am able to run it
< aneeshj>
I just built it
< zoq>
namrata_: So, since it was renamed in 2.0.2 you have to go with mlpack_allknn
< zoq>
namrata_: The README is for the latest version/git; so you have to pick the right one: http://www.mlpack.org/docs.html
< aneeshj>
zoq: I built from the master branch. Is that behind?
< namrata_>
aneeshj: I think it's because the version installed via apt-get is 2.0.1 and the renaming to mlpack_knn was done in 2.0.2 like zoq said.
< namrata_>
zoq: Thank you for the help
< aneeshj>
namrata_: ah right. Thanks
< zoq>
aneeshj: How large is this? I guess it could be helpful for others, maybe uploading it to dockerhup makes sense?
< aneeshj>
zoq: sure. I have installed it on a fresh Ubuntu 16 instance on virtualbox
< zoq>
ah, I thought you are using docker
< aneeshj>
docker images might cause trouble on the more gui based results
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< zoq>
aneeshj: Right, I guess you could forward X :) However, a Docker image might be intersting too, since mlpack has no GUI.
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< aneeshj>
zoq: I was thinking about the reinforcement learning related stuff. But I guess you're right, we can always forward it to a port
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< pawsed>
this is a Machine learning question more and less of a mlpack question, but how can recurrent networks be used for non-sequential data?
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< daivik>
zoq: I'm using a base ubuntu 16.04 docker image that has mlpack and its dependencies installed on top (along with some basic utilities like git, curl, python2/3 and the vim config from https://github.com/amix/vimrc). Mlpack is the latest dev version built from source, boost v1.62 and Armadillo 8.300 are also built from source. All other utilities a
< daivik>
re installed using the apt package manager. The image size is 3.79GB. This is probably because I've installed the entire boost library and some other utils that I do not recall as of now. The image size should go down by installing only the required boost libraries (unit_test_framework, math99, serialization, program_options, spirit). I'll be happy
< daivik>
to provide a Dockerfile/image for that if you think it would help other people.
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< desai-aditya>
Hey. I am getting 77 tests failed due to various errors like cannot open file , cannot load dataset, svd failed and fatal erros in adaboost. Build was the github build - master. Are they open issues or am I doing something wrong?
< daivik>
desai-aditya: the datasets are placed in the build directory after you run make
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< daivik>
if you run bin/mlpack_test from the build directory, you probably wont have problems like cannot load dataset,cannot open file etc
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< desai--aditya>
I tried do run tests from the build/bin/mlpack_test and it gave those errors .
< daivik>
right, cd into the build directory and run bin/mlpack_test
< desai--aditya>
Yes and doing that gave me those errors. It was built from the github master.
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< daivik>
can you see the datasets in your build directory when you do an ls?
< desai--aditya>
I'll check that and report back. Away from my machine right now sorry.
< daivik>
No problem
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< desai-aditya>
@daivik : I tried ls from the build directory and can find the datasets. They have read permissions for all - owner,group,root. The test gives this error - cannot load datasets.
< daivik>
what command are you giving to run the tests?
< daivik>
yeah, I think you;re using and old boost version .. are you on boost 1.58 or older?
< daivik>
this is actually exactly what I'm working on right now
< daivik>
*you're
< daivik>
*an
< daivik>
can you please check your boost version?
< desai-aditya>
Yes it's 1.58
< desai-aditya>
So I'm guessing I'll need to build boost from source too right? and armadillo?
< daivik>
yeah, you'll need to upgrade (I'm using boost 1.62, and I think all versions upto 1.66 are working) if you want to get rid of the errors -- I think you should upgrade if you want serialization to work properly. As for 1.58, while mlpack does support it, there are issues that need to be solved. As I said, I'm working on this right now.
< daivik>
Armadillo 6.500 and above should work fine
< daivik>
which I think you'll have already -- since there are no test failures related to armadillo
< desai-aditya>
I think I have arma 6.500
< daivik>
are you on ubuntu? and if so, did you install boost using apt-get?
< desai-aditya>
Yes correct.
< daivik>
ubuntu 16.04?
< daivik>
yeah, just build boost from souce
< daivik>
*source
< daivik>
after purging the existing installation
< desai-aditya>
ubuntu 16.04
< desai-aditya>
I think for the time being it should be mentioned in the documentation right?
< desai-aditya>
to update the docs I'll have to send a PR right?
< daivik>
I'm hoping to solve this soon, you can submit a PR if you want.
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< desai-aditya>
May I ask , how do you plan on solving it?
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< daivik>
Haha, that's a good question -- I'm still looking at various parts of the codebase. So, I've found that when boost 1.58 tries to load objects into type std::vector<arma::mat> it doesn't clear the vector -- instead just appends more objects. In v>=1.62, the vector is cleared. I'm fairly certain that the errors are related to this difference in behav
< daivik>
iors
< daivik>
rcurtin: are you there?
< yoloman>
Hello everyone,My name is Yash Sharan and I'm interested in participating for Gsoc 2018.I went through the tutorial mentioned on the mlpack website and have sucessfully built mlpack.The idea which I'm interested in working upon is resinforcement learning.I have been doing deep learning for a while and have also read about reinforcement learning and implemented a small project on it.Can anyone guide me on how to proceed further for th
< desai-aditya>
@yoloman : You can take a look at the open issues for a start related to your area of interest. check the github list of open issues.
< yoloman>
@desai-aditya.Thanks for the reply.However i checked the Gsoc ideas page and under this idea it says no issues are open right now related to this topic.
< desai-aditya>
You can start by getting familiar with the codebase. Try solving an open issue that you might like or try implementing something of your own.
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< robertohueso>
It might be a dumb question but... does anyone know where is "preprocess_split_main" binding_type set as BINDING_TYPE_TEST?
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