Ensemble Methods for Imbalanced Dataset
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Updated
Feb 5, 2020 - Jupyter Notebook
Ensemble Methods for Imbalanced Dataset
An R Package with Boosting and SMOTEBoost implementations for Regression Tasks
The pattern recognition assignments and solutions for fall 2019 by Dr. Analouei at Iran University of Science and Technology
We explore three algorithms and their combinations to tackle this problem of imbalance in the given dataset. Those algorithms are Gradient Boosting, SMOTE and Tomek Links. Each one is discussed in its own section.
An Scikit-learn compatible mini-library with implementations of the COBRA (Classifier) aggregator (that takes any sklearn classifier as an estimator, as opposed to pyCobra), and also provides the functionality of AdaBOOST and SMOTEBOOST. Oversampled Boosting is introduced for dealing with Class Imbalance Issues
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