SPegasos (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.

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Input Ports

  1. Type: Data Training data

Output Ports

  1. Type: Weka 3.7 Classifier Trained model

Find here

Analytics > Mining > Weka > Weka (3.7) > Classification Algorithms > functions

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