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Table of Contents
Abstract
1 Introduction
2 Methodology
2.1 Random Forest
2.2 Balanced Random Forest
2.3 Weighted Random Forest
3 Experiments
3.1 Data set
3.2 Performance Measurement
3.3 Performance Comparison
4 Conclusion
5 Acknowledgements
References
Summary
In this paper, two methods to deal with imbalanced data using random forest are proposed. The Balanced Random Forest and Weighted Random Forest techniques are discussed in detail along with their experiments and performance comparison results on various datasets. Both methods show favorable improvement over existing techniques. The conclusion highlights the effectiveness of these methods in handling imbalanced data.