Fuzzy k-NN classification with weights modified by most informative neighbors of nearest neighbors

Keyphrases

• Nearest Neighbor 100%
• Fuzzy k-NN 100%
• KNN Classification 100%
• Unknown Samples 60%
• Feature Vector 40%
• Membership Grade 40%
• Class Membership 40%
• Classification Accuracy 20%
• Convex Hull 20%
• Unlabeled Samples 20%
• Neighbour Type 20%
• Classification Rules 20%
• Classification Complexity 20%
• Labeled Sample 20%
• Nearest Neighbor Distance 20%
• Geometrical Relations 20%

Computer Science

• k-Nearest Neighbors Algorithm 100%
• Feature Vector 50%
• Membership Grade 50%
• Unlabeled Sample 25%
• Classification Rule 25%
• Classification Complexity 25%
• Classification Accuracy 25%