Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads�...
Abstract. Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quan-.
Two ways to make use of the few available novel patterns are proposed to determine local thresholds for the Self Organizing Map boundary and a modification�...
Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads�...
Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads�...
It has been empirically shown that a novelty detector trained with a few novel patterns as well can generate a more accurate and tighter boundary [9, 12] . In�...
Bibliographic details on SOM-Based Novelty Detection Using Novel Data.
Sep 14, 2007 � We describe a novel method for ligand-based virtual screening, based on utilizing Self-Organizing Maps (SOM) as a novelty detection device.
Novelty detection is the task of classifying test data that differ in some respect from the data that are available during training.
Novelty detection is the task of classifying test data that differ in some respect from the data that are available during training.