Kernel method for percentile feature extraction

Schölkopf, B; Platt, JC; Smola, AJ

Lokale TagsFreigabegeschichteDetailsÜbersicht

Kernel method for percentile feature extraction

Schölkopf, B., Platt, J., & Smola, A.(2000). Kernel method for percentile feature extraction (MSR-TR-2000-22). Redmond, WA, USA: Microsoft Research, Microsoft Corporation.

Item is Freigegeben

einblenden: alle ausblenden: alle

Basisdaten

einblenden: ausblenden:

Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E5E4-A Versions-Permalink: https://hdl.handle.net/21.11116/0000-0005-B6FB-3

Genre: Bericht

Dateien

einblenden: Dateien

Externe Referenzen

einblenden:

ausblenden:

externe Referenz:
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-2000-22.pdf (beliebiger Volltext) Open Access Status unbekannt

Beschreibung:
-

OA-Status:

Urheber

einblenden:

ausblenden:

Urheber:
Schölkopf, B¹, Autor
Platt, JC, Autor
Smola, AJ, Autor

Affiliations:
1External Organizations, ou_persistent22

Inhalt

einblenden:

ausblenden:

Schlagwörter: -

Zusammenfassung: A method is proposed which computes a direction in a dataset such that a specied fraction of a particular class of all examples is separated
from the overall mean by a maximal margin The pro jector onto that
direction can be used for classspecic feature extraction The algorithm
is carried out in a feature space associated with a support vector kernel
function hence it can be used to construct a large class of nonlinear fea
ture extractors In the particular case where there exists only one class
the method can be thought of as a robust form of principal component
analysis where instead of variance we maximize percentile thresholds Fi
nally we generalize it to also include the possibility of specifying negative
examples

Details

einblenden:

ausblenden:

Sprache(n):

Datum: Erschienen: 2000-02

Publikationsstatus: Erschienen

Seiten: -

Ort, Verlag, Ausgabe: Redmond, WA, USA : Microsoft Research, Microsoft Corporation

Inhaltsverzeichnis: -

Art der Begutachtung: -

Identifikatoren: Reportnr.: MSR-TR-2000-22
BibTex Citekey: 1836

Art des Abschluß: -

Datensatz

Basisdaten

Dateien

Externe Referenzen

Urheber

Inhalt

Details

Veranstaltung

Entscheidung

Projektinformation

Quelle