Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

nu-Anomica algorithm

Metadata Updated: December 7, 2023

One-class nu-Support Vector machine (SVMs) learning technique maps the input data into a much higher dimensional space and then uses a small portion of the training data (support vectors) to parametrize the decision surface that can linearly separate nu fraction of training points (labeled as anomalies) from the rest. The exact solution of standard one-class nu SVMs assigns (at least) nu fraction of training points as support vectors. However some of these support vectors may be unnecessary or redundant. Hence the computational issue turns alarming especially when SVMs based novelty detectors with nonlinear kernels are trained on data sets of huge size. The proposed nu-Anomica algorithm can solve this problem. The idea is to train the machine such that it can provide a close approximation to the exact decision plane using far less number of training points and without loosing much of the generalization performance of the classical approach. The developed procedure closely preserves the accuracy of standard One-class nu-SVMs while reducing both training time and test time by several factors.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources


Metadata Created Date November 12, 2020
Metadata Updated Date December 7, 2023
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date December 7, 2023
Publisher Dashlink
Identifier DASHLINK_131
Data First Published 2010-09-10
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id deac5c56-d8ae-4674-b5a1-fcb02e58e6a7
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL
Program Code 026:029
Source Datajson Identifier True
Source Hash 1a59004aeb2628acc54462357542649bbf4100d03733db4d39d713cbdc64d932
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.