logo oneClassClassifier

Performs one-class classification on a dataset. Classifier reduces the class being classified to just a single class, and learns the datawithout using any information from other classes. The testing stage will classify as 'target'or 'outlier' - so in order to calculate the outlier pass rate the dataset must contain informationfrom more than one class. Also, the output varies depending on whether the label 'outlier' exists in the instances usedto build the classifier. If so, then 'outlier' will be predicted, if not, then the label willbe considered missing when the prediction does not favour the target class. The 'outlier' classwill not be used to build the model if there are instances of this class in the dataset. It cansimply be used as a flag, you do not need to relabel any classes. For more information, see: Kathryn Hempstalk, Eibe Frank, Ian H. Witten: One-Class Classification by Combining Density and Class Probability Estimation. In: Proceedings of the 12th European Conference on Principles and Practice of Knowledge Discovery in Databases and 19th European Conference on Machine Learning, ECMLPKDD2008, Berlin, 505--519, 2008.

homepage: weka.sourceforge.net/doc.packages/oneClassClassifier
fresh index:
last release: 5 years ago, first release: 6 years ago
packaging: jar
get this artifact from: central
see this artifact on: search.maven.org

How much is this artifact used as a dependency in other Maven artifacts in Central repository and GitHub:
How many Android projects use it:

© Jiri Pinkas 2015 - 2018. All rights reserved. Admin login To submit bugs / feature requests please use this github page
related: JavaVids | Top Java Blogs | Java školení | 4npm - npm search | monitored using: sitemonitoring
Apache and Apache Maven are trademarks of the Apache Software Foundation. The Central Repository is a service mark of Sonatype, Inc.