it wasn't clear from the blog post but
are you aware that liblinear has a modification that handles sample weights
http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances
[fyi what I would be interested in (and I am not sure this is implemented
in that mod) is where one can aggregate the target]
ie in dealing with categorical data one would group over the input data,
weighting =group size and have target variable=average over group.
On Tue, Jul 29, 2014 at 2:03 AM, <
[email protected]> wrote:
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> Today's Topics:
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> 1. Re: Evaluation measure for imbalanced data (Yogesh Karpate)
> 2. [GSoC] - Logistic Regression CV (Manoj Kumar)
> 3. Re: RBK Kernel - Query (umang patel)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 29 Jul 2014 00:12:02 +0200
> From: Yogesh Karpate <[email protected]>
> Subject: Re: [Scikit-learn-general] Evaluation measure for imbalanced
> data
> To: [email protected]
> Message-ID:
> <
> cag7mfdsbnfqmqemddfxxzouhfhpnusbivjxcf1ozyegmvzu...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Dear Hamed,
> Can you share the code of "balanced accuracy" as you mentioned in last
> mail.
>
>
> On Tue, Jul 29, 2014 at 12:07 AM, Hamed Zamani <[email protected]>
> wrote:
>
> > Dear Mario,
> >
> > Yes of course. Sorry I forgot to mention GMeans. It is also one of the
> > measures which have been used frequently.
> >
> > -- Hamed
> >
> >
> >
> > On Tue, Jul 29, 2014 at 2:24 AM, Mario Michael Krell <
> [email protected]>
> > wrote:
> >
> >> Dear Hamed,
> >>
> >> I think it would be a good idea to also consider gmean when extending
> >> scikit. It is the geometric mean of TNR and TPR instead of the
> arithmetic
> >> mean used for the balanced accuracy.
> >>
> >> Greets
> >>
> >> Mario
> >>
> >> On 28.07.2014, at 19:00,
> >> [email protected] wrote:
> >>
> >> Dear Joel,
> >>
> >> Sorry for the delay. I was in a trip and I couldn't check my email.
> >>
> >> To the best of my knowledge and according to the kind responses in this
> >> email thread, we cannot claim that an specific measure is better than
> the
> >> others for imbalanced data. In other words, there are some evaluation
> >> measure suitable for imbalanced data and each of them has its own
> >> advantages. Hence, choosing the best evaluation measure totally depends
> on
> >> the application which you are working on.
> >>
> >> Anyway, "Matthew's Correlation Coefficient", "AUC of ROC", "F-measure",
> >> "Balanced Accuracy", and generally "Weighted Accuracy" have been used
> >> frequently in the literature. Among these measures, only "balanced
> >> accuracy" is not developed in scikit-learn and I think it is worthwhile
> to
> >> add it to this library. I have developed it before and if you want I can
> >> add it to the project or send it to you.
> >>
> >> Kind Regards,
> >> Hamed
> >>
> >>
> >>
> >>
> >>
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> >> _______________________________________________
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> >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> >>
> >>
> >
> >
> >
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>
> --
> Warm Regards
> Yogesh Karpate
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> ------------------------------
>
> Message: 2
> Date: Tue, 29 Jul 2014 01:38:44 +0200
> From: Manoj Kumar <[email protected]>
> Subject: [Scikit-learn-general] [GSoC] - Logistic Regression CV
> To: [email protected]
> Message-ID:
> <
> cafqad-nkckkapj8r8gez37pjd35ghwkwah_bd7s-avuhrfp...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi, A update on the new Logistic Regression CV model in scikit-learn
>
>
> http://manojbits.wordpress.com/2014/07/28/scikit-learn-logistic-regression-cv-2/
>
>
> --
> Regards,
> Manoj Kumar,
> GSoC 2014, Scikit-learn
> Mech Undergrad
> http://manojbits.wordpress.com
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> ------------------------------
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> Message: 3
> Date: Mon, 28 Jul 2014 20:02:56 -0400
> From: umang patel <[email protected]>
> Subject: Re: [Scikit-learn-general] RBK Kernel - Query
> To: [email protected]
> Message-ID:
> <
> camgx1excdd36fbnhxm_vmjry6adccnaesc3zpnxs5ojwn36...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Andy ,
>
> I nvr got answer . Could you please re- answer if possible . I will really
> appraciate it .
>
> Thank you.
>
>
>
> On Mon, Jul 28, 2014 at 2:53 PM, Andy <[email protected]> wrote:
>
> > Please do not repost.
> > You got an answer on the issue if I recall correctly.
> > If you want to know more, pick up a textbook on machine learning, such as
> > ESL (free pdf:
> > http://web.stanford.edu/~hastie/local.ftp/Springer/OLD/ESLII_print4.pdf
> ),
> > Kevin Murpy's book or the Bishop.
> >
> >
> > On 07/27/2014 08:22 PM, umang patel wrote:
> >
> > Hello all ,
> >
> > I asked the following question on "Issues" and I was advised to mail on
> > the following email id I i have furthur queries .
> >
> > "
> > Is it possible to get weight of features in rbf kernel .
> >
> > It is written under coeff_ that it is possible only with linear kernel .
> > Is it mathematically possible to get for rfb kernel , if yes then how ?
> > "
> >
> >
> > Could and one please direct me to relevant paper or please explain why
> it
> > is not possible to get coeff_ for rbf kernel .
> >
> > Thank you.
> >
> >
> > On Wed, Jul 23, 2014 at 8:33 AM, umang patel <[email protected]>
> > wrote:
> >
> >> Hello all ,
> >>
> >> I asked the following question on "Issues" and I was advised to mail
> on
> >> the following email id I i have furthur queries .
> >>
> >> "
> >> Is it possible to get weight of features in rbf kernel .
> >>
> >> It is written under coeff_ that it is possible only with linear kernel .
> >> Is it mathematically possible to get for rfb kernel , if yes then how ?
> >> "
> >>
> >>
> >> Could and one please direct me to relevant paper or please explain why
> >> it is not possible to get coeff_ for rbf kernel .
> >>
> >> Thank you.
> >>
> >
> >
> >
> >
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