build_fm {mildsvm} | R Documentation |
Build a feature map on new data
Description
Feature maps provide a set of covariates in a transformed space. The
build_fm()
function creates these covariates based on an object that
specifies the feature map and a provided dataset.
Usage
build_fm(kfm_fit, new_data, ...)
## S3 method for class 'kfm_exact'
build_fm(kfm_fit, new_data, ...)
## S3 method for class 'kfm_nystrom'
build_fm(kfm_fit, new_data, ...)
Arguments
kfm_fit |
An object from a function in the |
new_data |
The data to generate features from. |
... |
Additional arguments for methods. |
Value
A matrix of covariates in the feature space, with the same number of
rows as new_data
. If new_data
is a mild_df
object, build_fm()
will also return the columns containing 'bag_label', 'bag_name',
'instance_name'.
Methods (by class)
-
kfm_exact
: Method forkfm_exact
class. -
kfm_nystrom
: Method forkfm_nystrom
class.
Author(s)
Sean Kent
See Also
-
kfm_nystrom()
fit a Nystrom kernel feature map approximation. -
kfm_exact()
create an exact kernel feature map.
Examples
df <- data.frame(
X1 = c(2, 3, 4, 5, 6, 7, 8),
X2 = c(1, 1.2, 1.3, 1.4, 1.1, 7, 1),
X3 = rnorm(7)
)
fit <- kfm_nystrom(df, m = 7, r = 6, kernel = "radial", sigma = 0.05)
fm <- build_fm(fit, df)
fit <- kfm_exact(kernel = "polynomial", degree = 2, const = 1)
fm <- build_fm(fit, df)
[Package mildsvm version 0.4.0 Index]