NodeSPegasos (3.7)

Learner

Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al

(2007).This implementation globally replaces all missing values and transforms nominal attributes into binary ones.

It also normalizes all attributes, so the coefficients in the output are based on the normalized data.For more information, see

S.

Shalev-Shwartz, Y.Singer, N.

Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM.In: 24th International Conference on MachineLearning, 807-814, 2007.

(based on WEKA 3.7)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Input Ports

  1. Port Type: Data
    Training data

Output Ports

  1. Port Type: Weka 3.7 Classifier
    Trained model