rcurtin_irc changed the topic of #mlpack to: mlpack: a scalable machine learning library (https://www.mlpack.org/) -- channel logs: https://libera.irclog.whitequark.org/mlpack -- NOTE: messages sent here might not be seen by bridged users on matrix, gitter, or slack
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<zoq[m]> > <@gunnxx:gitter.im> Hi everyone, my name is Tri Wahyu Guntara, currently on my 2nd year of Master study in KAIST (Korea Advanced Institute of Science and Technology). I am a member of KAIST AIPR Lab working on Reinforcement Learning.... (full message at <https://libera.ems.host/_matrix/media/v3/download/libera.chat/a21ae2e637f55f63f0db294d599a4fa77687ef7b>)
<IWNMWEIWNMWE[m]> Hey guys as you know i was planning to put in a proposal for implementation of xgboost but someone has already given a proposal in the mailing list for it with some common objectives hence I would like to know about what would happen in such a case and if should stick to this idea or propose a different one
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<akhunti1[m]> Hi vaibhavp rcurtin
<akhunti1[m]> I got the out put like this :
<akhunti1[m]> If u see res is the dest data i gave using url command like this : curl -X POST -H 'Content-Type: application/json' -d '{"data": { "ndarray": [[1,2,3,4,5,6]]}}' http://localhost:9000/api/v1.0/predictions
<akhunti1[m]> ndarry is a dest data
<akhunti1[m]> but the accuracy mean prob i got 12 , expected is i should get 2 probability .
<akhunti1[m]> * got 12 point , expected
<rcurtin[m]> looks like the first two elements of the accuracy are the probability of the first class and the probability of the second class (i.e. the probability that it is not the first class :)); you can see that they sum to 1
<rcurtin[m]> IWNMWE (IWNMWE): that's okay, multiple people can submit applications for one project
<akhunti1[m]> rcurtin: Then why other 10 probality got created . because when i am giving same data point to cli it is giving me 2 probality . and both sum is 1 .
<rcurtin[m]> oh, I see what you mean now, sorry; what is the shape of the input matrix? mlpack's FFN will expect one point to correspond to one column (so it should have size 6 rows x 1 column), but if you gave that as 1 row x 6 columns, then the FFN will make predictions for 6 points, not one
<rcurtin[m]> if the shape is actually 1 row by 6 columns, just use .t() to transpose it to 6 rows by 1 column 👍️
<akhunti1[m]> #include "seldon/SeldonModel.hpp"... (full message at <https://libera.ems.host/_matrix/media/v3/download/libera.chat/06bfe5f10711483b3e00c25b0b3068cdfd002992>)
<rcurtin[m]> personally I don't have time to go through the code, you'll have to investigate the details, but the basic idea of what I wrote above should be correct
<akhunti1[m]> did u mean rf.Classify(arma::mat(res).t(), testPredictions,probs); [ if the shape is actually 1 row by 6 columns ]
<rcurtin[m]> yeah, that looks about right
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<akhunti1[m]> Hi sorry , but this way : rf.Classify(arma::mat(res).t(), testPredictions,probs); i am not able to transpose mat .
<akhunti1[m]> I also tried rf.Classify(arma::mat(res).st(), testPredictions,probs); .st() method , but did not work .
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<vaibhavp[m]> <akhunti1[m]> "Hi sorry , but this way : rf...." <- What error are you getting?
<akhunti1[m]> Hi vaibhavp i solved it by adding 91 .Thanks
<akhunti1[m]> * adding 91 to your given code .Thanks