Hyper Parameter Tuning for Random Forest in Python | Tutorial (Part 2/3)

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How to tune hyperparameters of a Random Forest Model in Python using Scikit Learn. The tutorial will provide a step-by-step guide for this.

Timestamp:
00:00​ - Introduction
00:47 - Import libraries & read data
01:40 - RandomizedSearchCV
06:54 - GridSearchCV
08:29​ - Create the final model
  1. Harsh Kumar
  2. Hyperparameter
  3. Hyperparam
  4. Hyperparameter Tuning
  5. Random Forest
  6. Python
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Комментарии
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This is a great tutorial ! Thank you so much for these details on random forest !

VauRDeC
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You have explained it very nicely, thanks for this tutorial

abhishekverma
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Thank's for your video, I have questions about "min_samples_split" and "min_samples_leaf" you have divided a thousand (/1000), where did you get it from the number 1000?

ardiansyahzainal
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Thank you so much for this work. How could you plot the chart between R-squared and number of estimators from 20-200?

vietttt
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Can you make one video, like how we use databases like Cassandra in Data science project

abhishekverma
visit shbcf.ru