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TinySVM specifications

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Unique identifier OMICS_15436
Name TinySVM
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java, Perl, Python, Ruby
License GNU General Public License version 3.0
Computer skills Advanced
Version 0.0.9
Source code URL http://www.chasen.org/~taku/software/TinySVM/src/TinySVM-0.09.tar.gz
Maintained Yes

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TinySVM citations

 (3)
library_books

Recognition of medication information from discharge summaries using ensembles of classifiers

2012
BMC Med Inform Decis Mak
PMCID: 3502425
PMID: 22564405
DOI: 10.1186/1472-6947-12-36

[…] the distance of the training samples nearest to it (called support vectors). svm takes as input a vector and maps it into a feature space using a kernel function [,]., in this paper we used tinysvm along with yamcha, developed at naist [,]. we used a polynomial kernel function of degree 2, a c-value of 1.0, and a context window of +/−2. the c-value controls the tradeoff between errors […]

library_books

Identification of transcription factor contexts in literature using machine learning approaches

2008
BMC Bioinformatics
PMCID: 2352869
PMID: 18426546
DOI: 10.1186/1471-2105-9-S3-S11

[…] detected. for most experiments we compare the results obtained from the two learning models (generic and biological) and three ml approaches (svm, nb, me). the svm classifier was built with the tinysvm package [] using the polynomial kernel, and the nb and me classifiers were implemented with mallet [] with the default parameters., as described earlier, we hypothesised that the descriptions […]

library_books

Gene/protein name recognition based on support vector machine using dictionary as features

2005
BMC Bioinformatics
PMCID: 1869022
PMID: 15960842
DOI: 10.1186/1471-2105-6-S1-S8

[…] the positive and negative examples. we report on the features that we used in our system to recognize gene/protein names. we use the yet another multipurpose chunk annotator, yamcha [], which uses tinysvm to bridge the gap between the results of feature extraction and the svm., training data (7500 sentences) and development test data (2500 sentences) were prepared for system development […]


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