Machine Learning Model Evaluation Metrics

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  • čas přidán 25. 07. 2024
  • MARIA KHALUSOVA | DEVELOPER ADVOCATE AT JETBRAINS
    Choosing the right evaluation metric for your machine learning project is crucial, as it decides which model you’ll ultimately use. Those coming to ML from software development are often self-taught, but practice exercises and competitions generally dictate the evaluation metric. In a real-world scenario, how do you choose an appropriate metric? This talk will explore the important evaluation metrics used in regression and classification tasks, their pros and cons, and how to make a smart decision.
  • Věda a technologie

Komentáře • 20

  • @diegosolis9681
    @diegosolis9681 Před 4 lety +37

    She was really nervous, and still could manage to give an excelente presentation filled with knowledge. That shows how much she actually know about the topic. Outstanding!

  • @kannan3801
    @kannan3801 Před 3 lety +12

    1.Classification -> 1:50
    a.Accuracy : 2:32
    b.Confusion Matrix : 4:37
    c.Precision : 7:39
    d.Recall : 8:21
    e.F1 score : 8:41
    2.Regression -> 24:44
    a.R^2 : 25:13
    b.MAE : 27:42
    c.MSE : 28:07
    d.RMSE : 28:22
    e.RMSLE : 31:31
    f.MAE VS RMSE : 29:10

  • @petrosiliadis5461
    @petrosiliadis5461 Před 4 lety +40

    Classification metrics -> 1:50
    Regression metrics ->24:43

  • @adamyatripathi2743
    @adamyatripathi2743 Před 4 lety +19

    Seemed a little nervous, but she nailed it. Amazing content and presentation!!

  • @karakol86
    @karakol86 Před 3 lety

    This material is available on her blog under her "Posts" section. One of the best summaries I have seen.

  • @kccchiu
    @kccchiu Před 3 lety +3

    Great content.
    I knew is gonna be a great presentation looking at her laptop.

  • @mimonwimoo4937
    @mimonwimoo4937 Před 3 lety +1

    great presentation! I wish my teacher explained like that... I learned so much from this, thank you!

  • @imagenigraphics
    @imagenigraphics Před 3 lety +1

    I can feel the tension but I understood what I was trying to learn. Thank you.

  • @ximo5628
    @ximo5628 Před 4 lety +1

    This is so great. Thanks!

  • @mikesmith1611
    @mikesmith1611 Před 5 lety +2

    Great summary 👍🏼

  • @ThiagoVieiratcvieira
    @ThiagoVieiratcvieira Před 4 lety +1

    love it!

  • @sanwalyousaf6405
    @sanwalyousaf6405 Před 3 lety

    This is such an interesting and engaging talk. Kudos

  • @KenoKanawa
    @KenoKanawa Před 2 lety

    Helped me thank you

  • @pakjuaan
    @pakjuaan Před 2 lety +2

    Thank you very much emma stone

  • @PanMarhewa
    @PanMarhewa Před 4 lety +1

    Looks like she was hardly stressed, but managed very well

  • @melissaznf1665
    @melissaznf1665 Před 3 lety

    Amazing content

  • @MegaThundergaming
    @MegaThundergaming Před 4 lety +2

    5:34 🙃👍

  • @lqtube
    @lqtube Před 3 lety +1

    nervous but great content

  • @arjungoud3450
    @arjungoud3450 Před 3 lety

    Better listen to every word she says, everything is informative

  • @aryamahima3
    @aryamahima3 Před 3 lety

    Great presentation...so well explained..however she seems disinterested in explaining..but thanks for the video..