#mlpack on 2021-06-08 — irc logs at libera.irclog.whitequark.org

2018-11-12 22:39 ChanServ changed the topic of #mlpack to: "mlpack: a fast, flexible machine learning library :: We don't always respond instantly, but we will respond; please be patient :: Logs at http://www.mlpack.org/irc/

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01:58 < jonpsy[m]> zoq: About the remote server, will it retain the files and dev-env setup? Also, who all have access to that server ? Because I might git-login there and it might be "not secure" if anyone other than us 3 have access to the server. Or perhaps there is a better way to go about this, let me know :)

01:59 < jonpsy[m]> oh ..and also, can i know the specs of the system, just excited :D

02:05 < zoq> jonpsy[m]: All files will be retained, yes; but probably not advisable to store secure information on the system, so I would not store e.g. the git credentials.

02:06 < jonpsy[m]> cool, about the specs.......?

02:06 < jonpsy[m]> btw sent the pub key in the doc 👍️

02:07 < zoq> jonpsy[m]: Intel(R) Core(TM) i7-7700 CPU @ 3.60GHz, 64GB RAM

02:07 < jonpsy[m]> Yoooooooooooooooo

02:07 < jonpsy[m]> sweet!

02:07 < zoq> jonpsy[m]: Will create the account tomorrow.

02:08 < zoq> jonpsy[m]: I guess we have to see if the latency is good enough for you.

02:08 < zoq> Hopefully it's not to bad.

02:08 < jonpsy[m]> Ah yes! If the server is in U.S that'd be problem

02:08 < jonpsy[m]> could you try banglore server?

02:08 < zoq> Germany.

02:09 < zoq> Canada might work as well.

02:09 < jonpsy[m]> canada is too far :)

02:09 < zoq> I'll setup the account, and we will see if it works, I guess.

02:10 < jonpsy[m]> is banglore server out of question...?

02:10 < jonpsy[m]> i suppose you'll have to pay again for it, correct?

02:10 < zoq> I don't have a machine in banglore :(

02:10 < jonpsy[m]> Bummer

02:11 < zoq> In this case the machine is a build node we use for jenkins as well, it's currently not really used.

02:11 < jonpsy[m]> Hmm, i mean if the training is fast (which shouldnt have to do with my latency), i can cope up with it.

02:12 < jonpsy[m]> germany works

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06:10 < HarshVardhanKuma> Hi guys. I'm having trouble with decision trees cli binding. It seems to reject the .bin file input (which I generated by loading a CSV file in armadillo as a matrix and then saving it). The same bin input file works with other mlpack cli bindings like random_forests and adaboost.

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08:13 < HarshVardhanKuma> Hi guys, there is one more doubt regarding mlpack_adaboost cli binding. It does not expose any option to choose the number of estimators - rather there is an option for the number of iterations. I suppose both are equivalent?

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10:18 < swaingotnochill[> zoq is there any way to store the dataset I will be working on server..

10:18 < swaingotnochill[> (edited) ... I will be working on server.. => ... I am working on server..?

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13:44 < zoq> swaingotnochill[: Which dataset are we talking?

13:45 < swaingotnochill[> I want to upload the California housing price dataset

13:47 < zoq> Ahh, there is no automated process for that, if you can post the link here, pretty sure @rcrutin can upload the dataset for you.

13:49 < swaingotnochill[> Okay...then let me just finish the first project..I will then ask Ryan to upload the dataset

13:50 < rcurtin[m]> yep, that's easy for me to do, but I don't have an automated script to do it... just send a URL and I'll add it to datasets.tar.gz :)

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14:15 < rcurtin[m]> hey, finally, successful docker matrix build: http://ci.mlpack.org/job/mlpack%20docker%20nightly%20build/48/ 😃

14:22 < rcurtin[m]> zoq: I'm looking at the `Select` layer right now... the comment is that it "selects the specified column from a given input matrix"---but in the ANN toolkit, a column is a single point in a batch. so is the idea here that we are reducing a batch to a single point? or should instead this be selecting a single dimension (or set of dimensions) from each input point?

14:22 < rcurtin[m]> I couldn't find any uses of the `Select` layer in the mlpack codebase, so I wasn't sure; maybe there are some uses in the examples or models repository though

14:24 < zoq> It will select a specific dimension, but honestly if there is no test for it, I would say let's remove the layer.

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14:25 < rcurtin[m]> oh, it is tested, but just as a standalone layer, not in the context of a larger network

14:25 < rcurtin[m]> I'll adapt it to use a specific dimension instead of a column 👍️

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14:30 < zoq> rcurtin[m]: looks like #49 is red because of some connection issue

14:30 < rcurtin[m]> yeah, I saw that... transient DNS failure on dealgood it seems like?

14:30 < rcurtin[m]> I'll watch and see if it keeps happening

14:31 < zoq> wondering if it makes sense to print out a warning and continue, because stb is optinal anyway

14:34 < rcurtin[m]> yeah, actually the better question is why STB isn't being detected on the system... I installed `libstb-dev`

14:34 < zoq> ohh you did, in this case yes that is the better question

14:42 < swaingotnochill[> zoq is there any way to read both the categorical and numerical data at same time?

14:43 < swaingotnochill[> zoq is there any way to read both the numerical and categorical data at the same time? the data::Load() only loads the numerical data.

14:44 < rcurtin[m]> zoq: oh! of course. I am running all this inside a docker container. so I just need to rebuild all the containers with stb inside them...

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15:04 < HarshVardhanKuma> I wanted to check if mlpack bindings have any option to run on multicores. I could not find any cli options for number of jobs. I wanted to know if it was possible?

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15:04 < rcurtin[m]> HarshVardhanKumar (Harsh Kumar): if you compile with OpenMP, or if you are using OpenBLAS, this will happen automatically (depending on the algorithm) :)

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15:05 < rcurtin[m]> also I saw your other messages... can you open an issue for the .bin problem you had with `mlpack_decision_tree`? and you are right that the number of iterations is the number of estimators for AdaBoost 👍️

15:15 < zoq> swaingotnochill[: You can read numerical and categorical data at the same time.

15:15 < jonpsy[m]> @zoq are you free rn?

15:15 < zoq> Example data - https://gist.githubusercontent.com/zoq/c92adb9e960ffc44d2de8cf41ad86137/raw/16005ef6fac4aeef6bab73a5ad0f37ad02a22494/test.csv

15:15 < zoq> example code to read the data - https://gist.github.com/zoq/8a0b2e755412a0ca4e3ce9529e001c7c

15:16 < zoq> this will print the numerical data and the categorical data as well

15:17 < zoq> jonpsy[m]: Sure

15:17 < swaingotnochill[> Thanks

15:18 < swaingotnochill[> One more thing to add @zoq

15:18 < swaingotnochill[> (edited) ... add @zoq => ... add zoq

15:19 < swaingotnochill[> Should I make a seperate notebook for cleaning and EDT of data and the actual algorithm?

15:20 < swaingotnochill[> Coz I read in the readme that the idea is to make the examples as short as possible.

15:20 < swaingotnochill[> (edited) ... and the actual algorithm? => ... and actual algorithm training?

15:21 < zoq> I would put it into a single notebook, would be confusing to split it up, if I e.g. have to run anther notebook to clean the data.

15:22 < jonpsy[m]> @zoq So i was thinking on starting with MOEA/D-DE first rather than SPEA-II

15:23 < jonpsy[m]> because a good amount of work is already done.

15:23 < zoq> jonpsy[m]: yes, was about to say that

15:23 < jonpsy[m]> Reading the paper gave me a shocking insight

15:24 < jonpsy[m]> wait, i'll just show you

15:24 < zoq> looks like you already digged into it quite a bit

15:25 < jonpsy[m]> PS => Pareto Set (i.e. in the variable space)

15:26 < jonpsy[m]> lemme know what you think abt it

15:28 < zoq> I mean it's true that the ZDT functions are simpler than the real world problems, but I think for benchmarking it's still relevant.

15:28 < jonpsy[m]> its not just ZDT

15:28 < jonpsy[m]> basically, the test-suites we've been building so far focus excessively of PF

15:29 < jonpsy[m]> * basically, the test-suites we've been building so far focus excessively on PF

15:29 < jonpsy[m]> bt their PS are way too simple, this is usually never the case in real life. (see second pic)

15:30 < jonpsy[m]> > basically, the test-suites we've been building so far focus excessively on PF

15:30 < jonpsy[m]> by testing various complicated shapes like : Convex, concave, multimodal, discontnuous

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15:31 < zoq> Sure, but I don't see the problem, we included them mainly for the purpose of using them inside the test suite.

15:31 < jonpsy[m]> i mean yeah

15:32 < zoq> No user will use ZDT to solve anything.

15:32 < jonpsy[m]> what im stressing at is "they're not enough"

15:32 < jonpsy[m]> > No user will use ZDT to solve anything.

15:32 < jonpsy[m]> yeah, same point.

15:33 < jonpsy[m]> so, these guys proposed a test-suite with complicated Pareto Sets .

15:33 < zoq> Don't mind to add some for further testing.

15:34 < zoq> If it dosn't take too long to optimize I'm fine with that.

15:34 < jonpsy[m]> yeah sure, but mainly, I was taken aback by ZDT PS being this simple.

15:34 < jonpsy[m]> that's what i wanted to point out

15:35 < zoq> Wondering if they just say that to make MOEA better.

15:35 < jonpsy[m]> hahaha, no. Their theory is sound.

15:36 < jonpsy[m]> aight, gotta jump, supper. Later then

15:36 < zoq> Also, the rocket problem is a good example, it's soemthing that is used in the real world.

15:36 < zoq> And I think this is something people like to see.

15:37 < zoq> ZDT is really abstract.

15:37 < zoq> That's why I like the rocket problem, it has a connection to the real world :)

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15:41 < jonpsy[m]> Yep, I plan to tackle MOEA/D-DE and rocket before first eval.

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18:59 < swaingotnochill[> Any idea why this error is popping up

18:59 < swaingotnochill[> ```error: use of undeclared identifier 'LinearRegression'```

18:59 < swaingotnochill[> I m just using LinearRegression<> lr( trainSet, trainLabels, 0.0);

19:00 < swaingotnochill[> zoq

19:00 < swaingotnochill[> Am i missing something?

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19:22 < zoq> swaingotnochill[: LinearRegression is not a template class - https://github.com/mlpack/mlpack/blob/master/src/mlpack/methods/linear_regression/linear_regression.hpp#L26

19:23 < zoq> let me know if that solves the issue

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19:56 < zoq> swaingotnochill[: https://gist.github.com/zoq/5b2ea05ad0719d5a95e4a14b0aa2c09d minimal example

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20:02 < swaingotnochill[> Ohh I see....I will make sure to check the methods file to make sure before using them..my error 😅

20:15 < swaingotnochill[> Yup...I didn't read the file...thought all method were implemented in same pattern...now when I see, its a class.

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