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LIBSVM specifications


Unique identifier OMICS_23789
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Version 3.22
Stability Stable
Source code URL
Maintained Yes


No version available


  • person_outline Chih-Jen Lin

Publication for LIBSVM

LIBSVM citations


Computer aided diagnosis for (123I)FP CIT imaging: impact on clinical reporting

PMCID: 5940985
PMID: 29740722
DOI: 10.1186/s13550-018-0393-5

[…] e for the ‘C’ hyperparameter in the SVM algorithm was selected through initial repeated, 10-fold cross-validation. Algorithm training was completed using Matlab software (Matlab, Natick, USA) and the libSVM library []. […]


Detection of cervical lymph node metastasis from oral cavity cancer using a non radiating, noninvasive digital infrared thermal imaging system

Sci Rep
PMCID: 5940875
PMID: 29739969
DOI: 10.1038/s41598-018-24195-4

[…] We used an SVM from libsvm tool to complete our experiments. The feature vectors acquired from images with lymphoma were assigned weight 1.2 while others were assigned weight 1.0. The penalty parameter of the error term […]


Decodability of Reward Learning Signals Predicts Mood Fluctuations

Curr Biol
PMCID: 5954908
PMID: 29706512
DOI: 10.1016/j.cub.2018.03.038

[…] llowing a 5-fold cross validation scheme. Training and testing sets were stratified such that the different sets included similar distributions of prediction errors. This analysis was performed using LIBSVM’s implementation [] of the ν-SVR algorithm [], whose parameters were fitted to each training set using a nested 5-fold-cross-validated grid search among the following settings: ν = [0.1 0.2 0.3 […]


Top down beta oscillatory signaling conveys behavioral context in early visual cortex

Sci Rep
PMCID: 5934398
PMID: 29725028
DOI: 10.1038/s41598-018-25267-1

[…] A linear Support-Vector-Machine (SVM) was implemented via libSVM to attempt to classify the spatial patterns of prestimulus top-down sGC according to which stimulus-response contingency (task rule) was in effect. The go response was the correct response to a […]


Neural Codes for One’s Own Position and Direction in a Real World “Vista” Environment

Front Hum Neurosci
PMCID: 5936771
PMID: 29760655
DOI: 10.3389/fnhum.2018.00167

[…] The overall classification procedure consisted in splitting the imaging data into two parts: a “training” set used to train a linear classifier (support vector machine (SVM); Duda et al., ) using the LIBSVM implementation (Chang and Lin, ) to identify patterns of activity related to the stimuli being discriminated, and an independent “test” set used to probe the classification accuracy. We tried t […]


Uses of selection strategies in both spectral and sample spaces for classifying hard and soft blueberry using near infrared data

Sci Rep
PMCID: 5923227
PMID: 29703949
DOI: 10.1038/s41598-018-25055-x

[…] y by committee and multiple views are used to rank the testing samples based on their informativeness. For comparison, the randomly ranked sample queue is also applied for modeling. Subsequently, the LIBSVM toolbox is adopted to classify hard and soft blueberries. The procedure of active learning for blueberry hardness classification is summarized in Fig. .Figure 10 […]


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LIBSVM institution(s)
Department of Computer Science, National Taiwan University, Taipei, Taiwan
LIBSVM funding source(s)
Supported by the National Science Council of Taiwan via the grants NSC 89-2213-E- 002-013 and NSC 89-2213-E-002-106.

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