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13 Random Forest

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Manage episode 273121440 series 2796489
Indhold leveret af Gustavo Lujan. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Gustavo Lujan eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Random Forest is one of the best out-of-the-shelf algorithms. In this episode we try to understand the intuition behind the Random Forest and how it tries to leverage the capabilities of Decision Trees by aggregating them using a very smart trick called “bagging”. Variable Importance and out-of-bag error are two of the nice capabilities of Random Forest which allow us to find the most important predictors and compute a good generalization error, respectively.

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20 episoder

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13 Random Forest

Machine Learning with Coffee

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Arkiveret serie ("Inaktivt feed" status)

When? This feed was archived on August 01, 2022 22:32 (1+ y ago). Last successful fetch was on February 18, 2022 09:16 (2y ago)

Why? Inaktivt feed status. Vores servere kunne ikke hente et gyldigt podcast-feed i en længere periode.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 273121440 series 2796489
Indhold leveret af Gustavo Lujan. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Gustavo Lujan eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Random Forest is one of the best out-of-the-shelf algorithms. In this episode we try to understand the intuition behind the Random Forest and how it tries to leverage the capabilities of Decision Trees by aggregating them using a very smart trick called “bagging”. Variable Importance and out-of-bag error are two of the nice capabilities of Random Forest which allow us to find the most important predictors and compute a good generalization error, respectively.

  continue reading

20 episoder

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