Transport new samples using learned FPGW alignment
Usage
# S3 method for class 'fpgw'
predict(
object,
newdata,
from,
to,
type = c("transport", "weights", "embedding"),
k = NULL,
...
)
Arguments
- object
An fpgw object
- newdata
New data from one domain to transport
- from
Source domain index or name
- to
Target domain index or name
- type
Type of prediction: "transport" (default), "weights", or "embedding"
- k
Number of nearest neighbors used for barycentric interpolation
- ...
Additional arguments
Value
Transported samples, barycentric weights, or embeddings (when implemented)
Details
This method provides out-of-sample extension for FPGW by:
Finding nearest neighbors in the source domain
Using the transport plan to map to target domain
Interpolating based on transport weights
The object must contain the training data used for fitting,
otherwise an error is thrown.
Examples
if (FALSE) { # \dontrun{
# After computing FPGW alignment
result <- fpgw(hd, omega1 = 0.1)
# Transport new samples from domain 1 to domain 2
new_samples <- matrix(rnorm(10 * 5), 10, 5)
transported <- predict(result, new_samples, from = 1, to = 2)
head(transported)
} # }