Monotonic Fuzzy k-Nearest Neighbors is an adaptation of the original Fuzzy k-NN for Monotonic Classification.

This repository includes the following files:

• skeel/classification/lazy_learning/MonFuzzyKNN: Main class of Monotonic Fuzzy k-NN. It extends MonKNN.
• skeel/classification/lazy_learning/FuzzyKNN: Implementation of the original Fuzzy k-NN
• skeel/classification/lazy_learning/KNN: Class implementing k-Nearest Neighbors for standard classification. It is needed by MonKNN class.
• skeel/classification/lazy_learning/MonKNN: Class of KNN for Monotonic classification. It extends KNN. It is needed by MonFuzzyKNN class.
• skeel/classification/Classifier: Scala trait to set the basics for every classifier.
• skeel/utils/Distance: Factory to compute the distance between two instances.
• skeel/utils/KeelDataset: Class to read and parse a dataset in KEEL format.
• skeel/utils/MonKeelDataset: Class to read and parse a dataset for monotonic classification in KEEL format.
• skeel/utils/Score: Class to compute the confusion matrix and different measurements giving the real and predicted class labels.
• skeel/utils/MonotonicScore: Class to compute different measurements of monotonic classification giving the real and predicted class labels. It extends Score class.

This proposal was accepted as a research paper in the journal Neurocomputing. ArXiv manuscript