aa901feeca
LIBLINEAR is a linear classifier for data with millions of instances
and features. It supports
L2-regularized classifiers
L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR)
L1-regularized classifiers (after version 1.4)
L2-loss linear SVM and logistic regression (LR)
L2-regularized support vector regression (after version 1.9)
L2-loss linear SVR and L1-loss linear SVR.
Main features of LIBLINEAR include
Same data format as LIBSVM, our general-purpose SVM solver,
and also similar usage
Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
Cross validation for model selection
Probability estimates (logistic regression only)
Weights for unbalanced data
MATLAB/Octave, Java, Python, Ruby interfaces
16 lines
791 B
Text
16 lines
791 B
Text
LIBLINEAR is a linear classifier for data with millions of instances
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and features. It supports
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|
L2-regularized classifiers
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|
L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR)
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L1-regularized classifiers (after version 1.4)
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L2-loss linear SVM and logistic regression (LR)
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L2-regularized support vector regression (after version 1.9)
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L2-loss linear SVR and L1-loss linear SVR.
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Main features of LIBLINEAR include
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Same data format as LIBSVM, our general-purpose SVM solver,
|
|
and also similar usage
|
|
Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
|
|
Cross validation for model selection
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|
Probability estimates (logistic regression only)
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Weights for unbalanced data
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MATLAB/Octave, Java, Python, Ruby interfaces
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