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Python implementation of "A Fuzzy K-nearest Neighbor Algorithm by J.M Keller, M.R. Grey and J.A. Givens" 📝
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sahilsehwag/FuzzyKNN
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This is a python implementation of Fuzzy KNN Algorithm. For more details or in-depth explanation look at this research paperA Fuzzy K-nearest Neighbor Algorithm by J.M Keller, M.R. Grey and J.A. Givens.
The main Fuzzy-KNN algorithm is implemented as a class namedFuzzyKNN, which resides in fknn.py.This class is implemented using scikit-learn's API.It inherits from BaseEstimator, ClassifierMixin and follows sklearn guidelines which allows it to be used as regular sklearnEstimator, making it useful as it can be used with sklearn's API.
A Jupyter Python Notebook is provided which also contains the implementation of FuzzyKNN for experimentation purposes. In this notebook accuracy of sklearn'sKNeighborsClassifier is compared with FuzzyKNN on toy datasets like IRIS and Breast Cancer.
If you like this repo, look at thismachine-learning-algorithms, where I implement various machine-learning algorithms as sklearnEstimators, and compares the accuracy of our custom implementation with sklearn's inbuilt implementations. Our custom implementations are commented for tutorial purposes, along with mathematics behind these algorithms.