score.apd_similarity {applicable} | R Documentation |
Score new samples using similarity methods
Description
Score new samples using similarity methods
Usage
## S3 method for class 'apd_similarity'
score(object, new_data, type = "numeric", add_percentile = TRUE, ...)
Arguments
object |
A |
new_data |
A data frame or matrix of new predictors. |
type |
A single character. The type of predictions to generate. Valid options are:
|
add_percentile |
A single logical; should the percentile of the similarity score relative to the training set values by computed? |
... |
Not used, but required for extensibility. |
Value
A tibble of predictions. The number of rows in the tibble is guaranteed
to be the same as the number of rows in new_data
. For type = "numeric"
,
the tibble contains a column called "similarity". If add_percentile = TRUE
,
an additional column called similarity_pctl
will be added. These values are
in percent units so that a value of 11.5 indicates that, in the training set,
11.5 percent of the training set samples had smaller values than the sample
being scored.
Examples
data(qsar_binary)
jacc_sim <- apd_similarity(binary_tr)
mean_sim <- score(jacc_sim, new_data = binary_unk)
mean_sim