6 search results - page 1 / 2 » Application of LVQ to novelty detection using outlier traini... |
PRL
2006
13 years 4 months ago
2006
We propose to use learning vector quantization (LVQ) in novelty detection where a few outliers exist in training data. The codebook update of original LVQ is modified and the sche...
FLAIRS
2004
13 years 6 months ago
2004
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
ESEM
2009
ACM
13 years 11 months ago
2009
ACM
Over the last 25+ years, the software community has been searching for the best models for estimating variables of interest (e.g., cost, defects, and fault proneness). However, li...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...
ICDM
2003
IEEE
13 years 10 months ago
2003
IEEE
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...