Communications of the ACM - Special issue on parallelism
Introduction to Grey system theory
The Journal of Grey System
Instance-Based Learning Algorithms
Machine Learning
Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Editing for the k-nearest neighbors rule by a genetic algorithm
Pattern Recognition Letters - Special issue on genetic algorithms
Prototype selection for the nearest neighbour rule through proximity graphs
Pattern Recognition Letters
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Selecting Examples for Partial Memory Learning
Machine Learning
Discovering Useful Concept Prototypes for Classification Based on Filtering and Abstraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting Typical Instances in Instance-Based Learning
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
Using Representative-Based Clustering for Nearest Neighbor Dataset Editing
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Data Mining for Case-Based Reasoning in High-Dimensional Biological Domains
IEEE Transactions on Knowledge and Data Engineering
An instance-based learning approach based on grey relational structure
Applied Intelligence
Finding Prototypes For Nearest Neighbor Classifiers
IEEE Transactions on Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Considerations about sample-size sensitivity of a family of editednearest-neighbor rules
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
The reduced nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
An algorithm for a selective nearest neighbor decision rule (Corresp.)
IEEE Transactions on Information Theory
The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.)
IEEE Transactions on Information Theory
Practical expert diagnosis model based on the grey relational analysis technique
Expert Systems with Applications: An International Journal
A fuzzy c-means clustering algorithm based on nearest-neighbor intervals for incomplete data
Expert Systems with Applications: An International Journal
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In pattern recognition, instance-based learning (also known as nearest neighbor rule) has become increasingly popular and can yield excellent performance. In instance-based learning, however, the storage of training set rises along with the number of training instances. Moreover, in such a case, a new, unseen instance takes a long time to classify because all training instances have to be considered when determining the 'nearness' or 'similarity' among instances. This study presents a novel reduced classification method for instance-based learning based on the gray relational structure. Here, only some training instances in the original training set are adopted for the pattern classification tasks. The relationships among instances are first determined according to the gray relational structure. In the relational structure, the inward edges of each training instance, indicating how many times each instance is considered as the nearest neighbor or neighbors in determining the class labels of other instances can be obtained. This method excludes training instances with no or few inward edges for the pattern classification tasks. By using the proposed instance pruning approach, new instances can be classified with a few training instances. Nine data sets are adopted to demonstrate the performance of the proposed learning approach. Experimental results indicate that the classification accuracy can be maintained when most of the training instances are pruned before learning. Additionally, the number of remained training instances in the proposal presented here is comparable to that of other existing instance pruning techniques.