We present a general, simple feature representation of sequences that allows efficient inexact matching, comparison and classification of sequential data. This approach, recently ...
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...
Prototype classifiers trained with multi-class classification objective are inferior in pattern retrieval and outlier rejection. To improve the binary classification (detection, v...
Abstract. A new classification algorithm based on combination of kernel density estimators is introduced. The method combines the estimators with different bandwidths what can be i...