predict.samHL

Predict decision values and class labels for test data.

Computationally efficient tools for high dimensional predictive
modeling (regression and classification). SAM is short for sparse
additive modeling, and adopts the computationally efficient basis
spline technique. We solve  the optimization problems by various
computational algorithms including the block coordinate descent
algorithm, fast iterative soft-thresholding algorithm, and newton method.
The computation is further accelerated by warm-start and active-set tricks.

Tuo Zhao

Sparse Additive Modelling

Haoming Jiang

Yukun Ma

Han Liu

Kathryn Roeder

Xingguo Li

predict.samHL function

<dl><dt>object</dt>
<dd>An object with S3 class <code>"samHL"</code>.</dd>
<dt>newdata</dt>
<dd>Numeric test matrix with <code>n</code> rows and <code>d</code> columns.</dd>
<dt>thol</dt>
<dd>Decision-value threshold used to convert scores to labels. The
default value is <code>0</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to methods; currently unused.</dd></dl>

Arguments

Prediction function for S3 class "samHL" — predict.samHL

<dl>

<dt>object</dt>
<dd>An object with S3 class <code>"samHL"</code>.</dd>


<dt>newdata</dt>
<dd>Numeric test matrix with <code>n</code> rows and <code>d</code> columns.</dd>


<dt>thol</dt>
<dd>Decision-value threshold used to convert scores to labels. The
default value is <code>0</code>.</dd>


<dt>...</dt>
<dd>Additional arguments passed to methods; currently unused.</dd>

</dl>

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

Description

Usage

Value

Arguments

Details

See Also