About: Margin-infused relaxed algorithm     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : el.dbpedia.org associated with source document(s)

Margin-infused relaxed algorithm (MIRA) is a machine learning algorithm, an online algorithm for multiclass classification problems. It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters according to each training example, so that the current training example is classified correctly with a margin against incorrect classifications at least as large as their loss. The change of the parameters is kept as small as possible. The flow of the algorithm looks as follows:

AttributesValues
rdfs:label
  • Margin-infused relaxed algorithm (en)
rdfs:comment
  • Margin-infused relaxed algorithm (MIRA) is a machine learning algorithm, an online algorithm for multiclass classification problems. It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters according to each training example, so that the current training example is classified correctly with a margin against incorrect classifications at least as large as their loss. The change of the parameters is kept as small as possible. The flow of the algorithm looks as follows: (en)
dbp:wikiPageUsesTemplate
Subject
prov:wasDerivedFrom
Wikipage page ID
page length (characters) of wiki page
Wikipage revision ID
Link from a Wikipage to another Wikipage
has abstract
  • Margin-infused relaxed algorithm (MIRA) is a machine learning algorithm, an online algorithm for multiclass classification problems. It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters according to each training example, so that the current training example is classified correctly with a margin against incorrect classifications at least as large as their loss. The change of the parameters is kept as small as possible. A two-class version called binary MIRA simplifies the algorithm by not requiring the solution of a quadratic programming problem (see below). When used in a configuration, binary MIRA can be extended to a multiclass learner that approximates full MIRA, but may be faster to train. The flow of the algorithm looks as follows: Algorithm MIRA Input: Training examples Output: Set of parameters ← 0, ← 0 for ← 1 to for ← 1 to ← update according to ← end for end for return * "←" denotes assignment. For instance, "largest ← item" means that the value of largest changes to the value of item. * "return" terminates the algorithm and outputs the following value. The update step is then formalized as a quadratic programming problem: Find , so that , i.e. the score of the current correct training must be greater than the score of any other possible by at least the loss (number of errors) of that in comparison to . (en)
foaf:isPrimaryTopicOf
is Wikipage redirect of
is Link from a Wikipage to another Wikipage of
is foaf:primaryTopic of
Faceted Search & Find service v1.17_git151 as of Feb 20 2025


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Nov 11 2024, on Linux (x86_64-ubuntu_focal-linux-gnu), Single-Server Edition (71 GB total memory, 2 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software