https://github.com/rmodi6/adaboost

Adaptive Boosting of Weak Learners implemented in Python
https://github.com/rmodi6/adaboost

adaboost adaptive-boosting-algorithm cross-validation empirical-risk-minimization machine-learning python38

Last synced: 12 months ago
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Adaptive Boosting of Weak Learners implemented in Python

• Host: GitHub
• URL: https://github.com/rmodi6/adaboost
• Owner: rmodi6
• License: mit
• Created: 2020-03-15T02:32:56.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-05-08T05:44:37.000Z (almost 6 years ago)
• Last Synced: 2025-01-11T08:09:01.028Z (about 1 year ago)
• Topics: adaboost, adaptive-boosting-algorithm, cross-validation, empirical-risk-minimization, machine-learning, python38
• Language: Jupyter Notebook
• Homepage:
• Size: 37.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Adaptive Boosting

The path to dataset can be provided using the `dataset` parameter and `mode` parameter can be used to specify the mode in which to execute adaboost. There are two modes available: `erm` for Empirical Risk Minimization and `cv` for 10 fold Cross Validation. For example:

```bash

python adaboost.py --dataset 'path/to/dataset' --mode erm

```