https://github.com/akarshankapoor7/adaboost_tutorial

The AdaBoost (Adaptive Boosting) algorithm is a popular ensemble method used in machine learning to improve the performance of weak classifiers. It combines multiple weak classifiers to create a strong classifier, focusing more on the misclassified instances in each subsequent iteration.
https://github.com/akarshankapoor7/adaboost_tutorial

adaboostclassifier data-science ensamble-methods

Last synced: 3 months ago
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The AdaBoost (Adaptive Boosting) algorithm is a popular ensemble method used in machine learning to improve the performance of weak classifiers. It combines multiple weak classifiers to create a strong classifier, focusing more on the misclassified instances in each subsequent iteration.

• Host: GitHub
• URL: https://github.com/akarshankapoor7/adaboost_tutorial
• Owner: akarshankapoor7
• Created: 2024-06-06T13:41:31.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-06-06T13:44:12.000Z (12 months ago)
• Last Synced: 2024-12-27T06:12:59.435Z (5 months ago)
• Topics: adaboostclassifier, data-science, ensamble-methods
• Language: Jupyter Notebook
• Homepage:
• Size: 491 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
This tutorial will tell you about the hyperparameter tuning in AdaBoost (Adaptive Boosting ) technique.