predict.l1svm

An object with S3 class <code>"l1svm"</code>.

object

The testing dataset represented in a <code>n</code> by <code>d</code> matrix, where <code>n</code> is sample size and <code>d</code> is dimension.

newdata

Predict the class labels for testing data.

The package SAM targets at high dimensional classification
        problem for complex data analysis. SAM is short for sparse
        additive machine, which is a explicit combination of high
        dimensional sparse additive modeling and support vector
        machine. Different from existing non-linear classification
        methods, which usually use, SAM adopts the computationally
        efficient basis spline technique. The optimization is solved by
        the Linearized Alternative Direction Method of Multipliers
        (L-ADMM). The computation is further accelerated by warm-start
        and active-set tricks. For users who are interested in
        large-scale problems, we also provide an implementation of L1
        norm SVM for computational convenience.

predict.l1svm: Prediction function for S3 class `"l1svm"`

Description

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