Random Forests Explanation and Visualization

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  • Опубликовано: 25 дек 2024

Комментарии • 15

  • @arkanasays
    @arkanasays 3 года назад +1

    very good explanation of random forest.

  • @kaganozdemir4332
    @kaganozdemir4332 4 года назад

    Best tutorial I've seen to clearly visualize and explain points that are taken for granted in other tutorials. Thanks!

  • @wobblyjelly345
    @wobblyjelly345 3 года назад +2

    Very helpful and informative prior to my exam, thank you!

  • @mdminhazurrahman8673
    @mdminhazurrahman8673 4 года назад

    i have seen many videos on random forest but this video clears me most about the concept.thank you

  • @bassabductor
    @bassabductor 3 года назад

    Simple and clear explanation. This help me in my studies!. Thank you.

  • @hombrefeliz7223
    @hombrefeliz7223 2 года назад

    Very well explained

  • @ownsaucee
    @ownsaucee 4 года назад

    Nice straightforward video explaining this, thank you!

  • @sahilsrivastava9895
    @sahilsrivastava9895 4 года назад +1

    Your video of Random forests is very helpful.

  • @leylam.5920
    @leylam.5920 4 года назад

    Very good explanation

  • @itmisc2007
    @itmisc2007 4 года назад

    Nice explanation!

  • @fadiabougacha2220
    @fadiabougacha2220 4 года назад

    Thank you for your response.
    For the second part of my question, I would like to know why the size of the bootstrap for each decision tree is not equal to the size of the original database.
    Also, I have another question. I saw that for the random forest, the two criteria to measure the importance of each variable are: Mean Decrease Accuracy and Mean Decrease Gini. my question how to calculate the Mean Decrease Accuracy and Mean Decrease Gini (formula)
    Thank you,

  • @fadiabougacha2220
    @fadiabougacha2220 4 года назад

    For random forest, I would like to know you have to make a bootstap from the original database or just a draw without replacement. Does the size for each sample equal the size of the original database

    • @TheDataPost
      @TheDataPost  4 года назад +1

      Hi Fadia,
      I believe bootstrapping is the default behavior for most implementations; however, you'll have to look specifically at the library you're using. SKlearn for example bootstraps by default but it can be turned off at your discretion... I always leave bootstrapping on. As for the second part of your question about sample size, I don't fully understand. If you rephrase it I may be able to shed light.
      Best,
      TheDataPost

  • @bhavaniblessy257
    @bhavaniblessy257 4 года назад

    Nice..please send the ppt