Results 231 to 240 of about 84,282 (259)
Some of the next articles are maybe not open access.
Hybrid k -Nearest Neighbor Classifier.
IEEE transactions on cybernetics, 2016Conventional k -nearest neighbor (KNN) classification approaches have several limitations when dealing with some problems caused by the special datasets, such as the sparse problem, the imbalance problem, and the noise problem. In this paper, we first perform a brief survey on the recent progress of the KNN classification approaches.
Zhiwen Yu 0002 +5 more
openaire +2 more sources
A Centroid k-Nearest Neighbor Method
2010K-nearest neighbor method (KNN) is a very useful and easy-implementing method for real applications. The query point is estimated by its K nearest neighbors. However, this kind of prediction simply uses the label information of its neighbors without considering their space distributions.
Qingjiu Zhang, Shiliang Sun
openaire +1 more source
Robustness Certification of k-Nearest Neighbors
2023 IEEE International Conference on Data Mining (ICDM), 2023Nicolò Fassina +2 more
openaire +1 more source
Classification Bias of the k-Nearest Neighbor Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984The k-nearest neighbor classifier has been used extensively in pattern analysis applications. This classifier can, however, have substantial bias when there is little class separation and the sample sizes are unequal. This classification bias is examined for the two-class situation and formulas presented that allows selection of values of k that yields
openaire +2 more sources
A representation coefficient-based k-nearest centroid neighbor classifier
Expert Systems With Applications, 2022Weihua Ou +2 more
exaly
A new two-layer nearest neighbor selection method for kNN classifier
Knowledge-Based Systems, 2022Zhibin Pan
exaly
Locally nearest neighbor classifiers for pattern classification
Pattern Recognition, 2004Wenming Zheng, Cairong Zou
exaly