Download datasets

[vinhqdang]

Hello there

Is there a place that I can download the datasets you used in the paper? I tried with Google but it seems quite diverse.

Thanks

[vinhqdang]

Hello there,

It seems to me that the function 'one_class_data' does not exist at all in sklearn.

http://scikit-learn.org/stable/datasets/index.html

How did you use that before?

Thanks

[xingfengzhang]

hi ,have u haddle it?

[ngoix]

Hi, sorry this code is not maintained. you can find the function here: https://github.com/ngoix/OCRF/blob/master/sklearn/datasets/one_class_data.py
not sure which version of sklearn it can handle but using 0.17 should be ok

[xingfengzhang]

ok ,thanks~ And then,the Repository: EMMV_benchmarks is also the code associated with the ICML paper,right? and i can use the function of EM and MV of module em.py，right? Looking forward to your relpy ,please~ best wishes~ ------------------ 原始邮件 ------------------ 发件人: "Nicolas Goix"<[email protected]>; 发送时间: 2019年6月9日(星期天) 凌晨1:54 收件人: "ngoix/EMMV_benchmarks"<[email protected]>; 抄送: "张兴凤"<[email protected]>;"Comment"<[email protected]>; 主题: Re: [ngoix/EMMV_benchmarks] Download datasets (#1) Hi, sorry this code is not maintained. you can find the function here: https://github.com/ngoix/OCRF/blob/master/sklearn/datasets/one_class_data.py not sure which version of sklearn it can handle but using 0.17 should be ok — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or mute the thread.

[ngoix]

Yes, that is right.

…

On Mon, Jun 10, 2019, 04:23 xingfengzhang ***@***.***> wrote: ok ,thanks~ And then,the Repository: EMMV_benchmarks is also the code associated with the ICML paper,right? and i can use the function of EM and MV of module em.py，right? Looking forward to your relpy ,please~ best wishes~ ------------------ 原始邮件 ------------------ 发件人: "Nicolas ***@***.***>; 发送时间: 2019年6月9日(星期天) 凌晨1:54 收件人: ***@***.***>; 抄送: ***@***.******@***.***>; 主题: Re: [ngoix/EMMV_benchmarks] Download datasets (#1) Hi, sorry this code is not maintained. you can find the function here: https://github.com/ngoix/OCRF/blob/master/sklearn/datasets/one_class_data.py not sure which version of sklearn it can handle but using 0.17 should be ok — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or mute the thread. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#1?email_source=notifications&email_token=ABLLKAN3MHZMLKSSW2AS5MLPZW3LTA5CNFSM4FFNEBOKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXIYPJQ#issuecomment-500271014>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABLLKAJTAB4TYIVO5IF7IKDPZW3LTANCNFSM4FFNEBOA> .

[xingfengzhang]

OK,thanks very much~ and then,I still have one question. The optimal (also maximum) AUC (the area under EM curve) is 1,according to the definition of EM curve,right? Looking forward to your relpy ,please~

…

------------------ 原始邮件 ------------------ 发件人: "Nicolas Goix"<[email protected]>; 发送时间: 2019年6月12日(星期三) 下午2:36 收件人: "ngoix/EMMV_benchmarks"<[email protected]>; 抄送: "张兴凤"<[email protected]>;"Comment"<[email protected]>; 主题: Re: [ngoix/EMMV_benchmarks] Download datasets (#1) Yes, that is right. On Mon, Jun 10, 2019, 04:23 xingfengzhang <[email protected]> wrote: ok ,thanks~ And then,the Repository: EMMV_benchmarks is also the code associated with the ICML paper,right? and i can use the function of EM and MV of module em.py，right? Looking forward to your relpy ,please~ best wishes~ ------------------ 原始邮件 ------------------ 发件人: "Nicolas Goix"<[email protected]>; 发送时间: 2019年6月9日(星期天) 凌晨1:54 收件人: "ngoix/EMMV_benchmarks"<[email protected]>; 抄送: "张兴凤"<[email protected]>;"Comment"<[email protected]>; 主题: Re: [ngoix/EMMV_benchmarks] Download datasets (#1) Hi, sorry this code is not maintained. you can find the function here: https://github.com/ngoix/OCRF/blob/master/sklearn/datasets/one_class_data.py not sure which version of sklearn it can handle but using 0.17 should be ok — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or mute the thread. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#1?email_source=notifications&email_token=ABLLKAN3MHZMLKSSW2AS5MLPZW3LTA5CNFSM4FFNEBOKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXIYPJQ#issuecomment-500271014>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABLLKAJTAB4TYIVO5IF7IKDPZW3LTANCNFSM4FFNEBOA> . — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or mute the thread.