Metric learning by discriminant neighborhood embedding
Pattern Recognition
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Metric Learning: A Support Vector Approach
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Graph-Based Discrete Differential Geometry for Critical Instance Filtering
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Constructing ensembles of classifiers by means of weighted instance selection
IEEE Transactions on Neural Networks
Hierarchical Multi-view Fisher Discriminant Analysis
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Kernel-based metric learning for semi-supervised clustering
Neurocomputing
Classification Using Geometric Level Sets
The Journal of Machine Learning Research
Soft Nearest Convex Hull Classifier
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Edited AdaBoost by weighted kNN
Neurocomputing
Dynamic time warping constraint learning for large margin nearest neighbor classification
Information Sciences: an International Journal
Learning low-rank kernel matrices for constrained clustering
Neurocomputing
Improved support vector machines with distance metric learning
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Adaptive nearest neighbor classifier based on supervised ellipsoid clustering
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Learning from pairwise constraints by Similarity Neural Networks
Neural Networks
Image classification based on weighted topics
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
k nearest neighbor using ensemble clustering
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Adaptive distance metrics for nearest neighbour classification based on genetic programming
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
An ensemble-clustering-based distance metric and its applications
International Journal of Business Intelligence and Data Mining
| Hi-index | 0.00 |
The nearest neighbor technique is a simple and appealing approach to addressing classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with a finite number of examples due to the curse of dimensionality. Severe bias can be introduced under these conditions when using the nearest neighbor rule. The employment of a locally adaptive metric becomes crucial in order to keep class conditional probabilities close to uniform, thereby minimizing the bias of estimates. We propose a technique that computes a locally flexible metric by means of support vector machines (SVMs). The decision function constructed by SVMs is used to determine the most discriminant direction in a neighborhood around the query. Such a direction provides a local feature weighting scheme. We formally show that our method increases the margin in the weighted space where classification takes place. Moreover, our method has the important advantage of online computational efficiency over competing locally adaptive techniques for nearest neighbor classification. We demonstrate the efficacy of our method using both real and simulated data.