Evidence map›Paper›PMID 24459436›Full record

ArticleTheScientificWorldJournal2013

The generalization error bound for the multiclass analytical center classifier.

Zeng Fanzi, Ma Xiaolong

Abstract read
In one paragraph

Article in TheScientificWorldJournal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Zeng FanziKey Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, Changsha 410082, China.
Ma XiaolongKey Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, Changsha 410082, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents the multiclass classifier based on analytical center of feasible space (MACM). This multiclass classifier is formulated as quadratic constrained linear optimization and does not need repeatedly constructing classifiers to separate a single class from all the others. Its generalization error upper bound is proved theoretically. The experiments on benchmark datasets validate the generalization performance of MACM.

Indexed as

AlgorithmsArtificial IntelligenceClassificationDatabases, FactualHumansLinear ModelsModels, StatisticalSupport Vector Machine

Identifiers

PMID24459436
PMCPMC3891430

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.