LIBSVM: A library for support vector machines
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47,974 citations
Cites methods from "LIBSVM: A library for support vecto..."
...While the package is mostly written in Python, it incorporates the C++ libraries LibSVM (Chang and Lin, 2001) and LibLinear (Fan et al....
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19,603 citations
Cites methods from "LIBSVM: A library for support vecto..."
...• Wrapper classifiers: allow the well known algorithms provided by the LibSVM [5] and LibLINEAR [9] thirdparty libraries to be used in WEKA....
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...Supported .le formats include WEKA s own ARFF format, CSV, LibSVM s format, and C4.5 s format....
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...6 is the ability to read and write data in the format used by the well known LibSVM and SVM-Light support vector machine implementations [5]....
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...This complements the new LibSVM and LibLIN-EAR wrapper classi.ers....
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...Wrapper classi.ers: allow the well known algorithms provided by the LibSVM [5] and LibLINEAR [9] thirdparty libraries to be used in WEKA....
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11,283 citations
Cites methods from "LIBSVM: A library for support vecto..."
...We found that for the classification task SVMs [11] clearly outperform nearest neighbor classification....
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...All Classification Similarity SVM[11] 0....
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10,696 citations
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References
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"LIBSVM: A library for support vecto..." refers methods in this paper
...Domain Computer vision Natural language processing Neuroimaging Bioinformatics Representative works LIBPMK [Grauman and Darrell 2005] Maltparser [Nivre et al. 2007] PyMVPA [Hanke et al. 2009] BDVal [Dorff et al. 2010] A typical use of LIBSVM involves two steps: .rst, training a dataset to obtain a model and second, using the model to predict information of a testing dataset....
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...…Neuroimaging Bioinformatics Representative works LIBPMK [Grauman and Darrell 2005] Maltparser [Nivre et al. 2007] PyMVPA [Hanke et al. 2009] BDVal [Dorff et al. 2010] A typical use of LIBSVM involves two steps: .rst, training a dataset to obtain a model and second, using the model to predict…...
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...BDVal: reproducible large-scale predictive model development and validation in high-throughput datasets....
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