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mamas16k's profile
まます
まます
まます
@mamas16k

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まます

@mamas16k

シナモン/囲碁(東洋7段, kgs6d)/sm64 hack/kaggle

kgs go server
kaggle.com/mamasinkgs
Joined December 2010

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    まます‏ @mamas16k May 18

    たとえば精度を上げるアイデアが10個あって、それをちゃんとtrain/val/testに切った上で評価して、どれか一つのアイデアが当たって論文にしたとする。そこで「それはお前が10回もtest set見たからだろ?」って言われたらどうするんだろう

    2:43 AM - 18 May 2019
    • 50 Retweets
    • 176 Likes
    • ターヤ Machine_Learning_Taro 西尾 理志 もりのすけ 機械学習おじさん アライ(バ) koichi@ロンドン理系大学院留学 t.mimori まきの たかき
    2 replies 50 retweets 176 likes
      1. New conversation
      2. まます‏ @mamas16k May 18

        なんか表現が下手だが、「論文の本数」= 「自分の主張する手法をtest setで評価した回数」 になってない人は厳密には全員アウトじゃね?ってのが言いたいこと

        1 reply 5 retweets 20 likes
        Show this thread
      3. まます‏ @mamas16k May 18

        一回でも提案手法がボツになってしまった時点でもうその人の主張はアテにならないのでは?

        1 reply 1 retweet 7 likes
        Show this thread
      4. まます‏ @mamas16k May 18

        private LBなしのtrain/val/test教は最終的にこのふざけた結論に辿り着くのでダメと思ってる。誰かこの主張が伝わって欲しい

        0 replies 2 retweets 27 likes
        Show this thread
      5. End of conversation
      1. New conversation
      2. HELLO CYBERNETICS‏ @ML_deep May 18
        Replying to @mamas16k @azriel1rf

        アイデア1個をtrain/val/testで評価して、駄目だったら次……を10回繰り返すのではなく、 アイデア10個をtrain/valでチューニングした後に、10個のアイデアを同時にtestで評価ならOKってことですか?

        2 replies 1 retweet 4 likes
      3. まます‏ @mamas16k May 18
        Replying to @ML_deep @azriel1rf

        もちろん理想的にはそうするのが正しいわけですが、それを行うためには「前以てアイデアを全て思いついておく必要がある」 という非現実的な仮定が必要になってしまいます。(後から新しいアイデアが出てきたらもうアウト)

        2 replies 1 retweet 7 likes
      4. まます‏ @mamas16k May 18
        Replying to @mamas16k @ML_deep @azriel1rf

        「test setでearly stoppingは論外!」とか言ってる人がいますが、結局新しいアイデアが出た時点でもうアウトなのは同じなので、train/val/testみたいな「正しいやり方」と本質的にはそんな変わらんだろ、みたいなのが自分の言いたい内容です(表現が難しいけど伝わって欲しい)

        0 replies 3 retweets 7 likes
      5. End of conversation

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