Search Results for author:
Found 4 papers, 0 papers with code
Scalable Prototype Selection by Genetic Algorithms and Hashing
In this paper we proposed scalable methods to select the set of prototypes out of very large datasets.
Fast kNN mode seeking clustering applied to active learning
A drawback of using the clustering for classification, however, is that no classifier is obtained that may be used for out-of-sample objects.
Domain based classification
The majority of traditional classification ru les minimizing the expected probability of error (0-1 loss) are inappropriate if the class probability distributions are ill-defined or impossible to estimate.
Zero-error dissimilarity based classifiers
We consider general non-Euclidean distance measures between real world objects that need to be classified.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
