Reference: S. S. Mullick, S. Datta and S. Das, "Adaptive Learning-Based k-Nearest Neighbor Classifiers With Resilience to Class Imbalance," in IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2018.2812279.
Contact: [email protected] (Sankha Subhra Mullick).
- The package contains 7 functions.
- adaKnn.m: Function implementing Ada-kNN algorithm.
- adaKnn2.m: Function implementing Ada-kNN2 algorithm.
- adaKnnGIHS.m: Function implementing Ada-kNN coupled with GIHS algorithm (for imbalanced classification).
- adaKnn2GIHS.m: Function implementing Ada-kNN coupled with GIHS algorithm (for imbalanced classification).
- kNNIMB.m: Function implementing weighted k-nearest neighbor algorithm.
- learningModel.m: Function implementing the proposed heuristic learning technique (to be used by adaKnn2 and adaKnn2GIHS).
- standardised.m: Supporting function.
- MATLAB 2014a and above.
- Neural Network toolbox (for adaKnn and adaKnnGIHS).