Search: id:"swepub:oai:DiVA.org:kth-129602" >
Properties of Datas...
-
Aghazadeh, Omid,1982-KTH,Datorseende och robotik, CVAP,Computer Vision Group
(author)
Properties of Datasets Predict the Performance of Classifiers
- Article/chapterEnglish2013
Publisher, publication year, extent ...
-
British Machine Vision Association, BMVA,2013
-
printrdacarrier
Numbers
-
LIBRIS-ID:oai:DiVA.org:kth-129602
-
https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129602URI
-
https://doi.org/10.5244/C.27.44DOI
Supplementary language notes
-
Language:English
-
Summary in:English
Part of subdatabase
Classification
-
Subject category:ref swepub-contenttype
-
Subject category:kon swepub-publicationtype
Notes
-
QC 20140602
-
It has been shown that the performance of classifiers depends not only on the number of training samples, but also on the quality of the training set [10, 12]. The purpose of this paper is to 1) provide quantitative measures that determine the quality of the training set and 2) provide the relation between the test performance and the proposed measures. The measures are derived from pairwise affinities between training exemplars of the positive class and they have a generative nature. We show that the performance of the state of the art methods, on the test set, can be reasonably predicted based on the values of the proposed measures on the training set. These measures open up a wide range of applications to the recognition community enabling us to analyze the behavior of the learning algorithms w.r.t the properties of the training data. This will in turn enable us to devise rules for the automatic selection of training data that maximize the quantified quality of the training set and thereby improve recognition performance.
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
-
Carlsson, StefanKTH,Datorseende och robotik, CVAP,Computer Vision Group(Swepub:kth)u1agqz5q
(author)
-
KTHDatorseende och robotik, CVAP
(creator_code:org_t)
Related titles
-
In:BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013: British Machine Vision Association, BMVA
Internet link
To the university's database