... (b)
(c) (d)
1
Gene Selection for Cancer Classification using
Support Vector Machines
Isabelle Guyon+, Jason Weston+, Stephen Barnhill, M.D.+
and Vladimir Vapnik*
+Barnhill Bioinformatics, Savannah, ... be
computed for support vectors only, which makes it affordable for small numbers
of support vectors. Additionally, parts of the calculation such as the dot products
x...
... pages 25–30,
Prague, June 2007.
c
2007 Association for Computational Linguistics
Automatic Prediction of Cognate Orthography Using
Support Vector Machines
Andrea Mulloni
Research Group in Computational ... of the major ML-
based taggers available, we decided to opt for
SVMTool, a generator of sequential taggers based
on Support Vector Machines developed by
Gimenez and Ma...
...
Space
Feature
vector
Fig. 5 ANN for classifying
Fig. 6 Image classification using ANN_SVM model
36 Image Classification using Support Vector Machine and Artificial ... applying for facial expression
classification, and Multi Classifier Scheme applying for
Adult image classification.
MANN model are shown in the following diagram:
Image Class...
... words, using sequences of POS tags to capture
rough syntactic information. The resulting vocabu-
lary consisted of 276 words and 56 POS tags.
4.3 Support Vector Machines
Support vector machines ... perplexity.
4.2 Feature Selection
Feature selection is a common part of classifier
design for many classification problems; however,
there are mixed results in the literature on f...
... paper presents the use of Support
Vector Machines (SVM) to detect rele-
vant information to be included in a query-
focused summary. Several SVMs are
trained using information from pyramids
of ... extraction models for the summary au-
tomatic construction. This paper describes several
models trained from the information in the DUC-
2006 manual pyramid annotations using Support...
... Sup-
port Vector Machines (SVMs) because of their per-
formance.
The Support Vector Machine, which is introduced
by Vapnik (1995), is a powerful new statistical learn-
ing method. Excellent performance ... solving the following optimiza-
tion problem:
maximize
subject to
3 Active Learning for Support Vector
Machines
3.1 General Framework of Active Learning
We use pool-based ac...
... Data point selection
The key idea in our experiments is that we can use a
simple form of instance weighting, similar to what is
often used for correcting sample selection bias or for
domain adaptation, ... remaining data we use. For example, for Bulgar-
ian our baseline result using 100% of the source data
is 44.5%, and the result obtained using 90% of the
source data is 70.2%...
... Filters through
Latent Support Vector Machines
Colin Cherry
Institute for Information Technology
National Research Council Canada
colin.cherry@nrc-cnrc.gc.ca
Shane Bergsma
Center for Language and Speech ... of
the time for parsing is spent scoring each poten-
tial arc in the complete dependency graph (John-
son, 2007), one for each ordered word-pair in the
sentence. Potential ar...