https://github.com/balaka-18/ensembles-1-
Notebooks on ensemble techniques.
https://github.com/balaka-18/ensembles-1-
bagging-ensemble classification random-forest random-forest-classifier
Last synced: 11 months ago
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Notebooks on ensemble techniques.
- Host: GitHub
- URL: https://github.com/balaka-18/ensembles-1-
- Owner: BALaka-18
- License: mit
- Created: 2020-07-21T11:53:47.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-11-19T21:36:57.000Z (over 5 years ago)
- Last Synced: 2025-06-06T23:08:44.547Z (12 months ago)
- Topics: bagging-ensemble, classification, random-forest, random-forest-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 50.8 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Ensemble Techniques
Notebooks on different ensemble techniques and the algorithm behind them, both Bagging and Boosting.
BAGGING (Bootstrap AGGregation)
Notebook 1 : RandomForestClassifier() class from scratch.
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BOOSTING
*Algorithm 1 : AdaBoost (Adaptive boosting)*
Notebook 1 : AdaboostClassifier() class from scratch. Shows valid working example on a chosen query point.
Notebook 2 : Comparison between the performance of scikit-learn's AdaboostClassifier() and the Adaboost classifier created from scratch(in [Notebook 1](https://github.com/BALaka-18/Ensembles-1-/blob/master/Adaboost_from_Scratch.ipynb)), by plotting their decision boundaries on the [play_tennis.csv](https://www.kaggle.com/fredericobreno/play-tennis) dataset.
Screenshot :
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