This is the constructor of the featscreen
class.
Usage
featscreen(
method = c("cor.test", "t.test", "w.test", "anova", "kruskal.wallis", "chisq.test",
"coxph", "moderated.t", "moderated.F", "sam.test", "missing.value", "above.median",
"above.minimum", "median", "variability"),
multi = character(),
selection = c("cutoff", "rank", "percentile", "fpr", "fdr"),
summary = character(),
n = integer(),
features = character(),
keep = vector(),
ranks = integer()
)
Arguments
- method
character string, the id of the used screening method.
- multi
(optional) character string, the id of the used multi-response aggregation method.
- selection
character string, the id of the used selection method.
- summary
character string, a textual summary of the screening.
- n
integer, the dimension of the feature space.
- features
string vector, the names of the features constituting the feature space.
- keep
integer or logical vector, the features to keep.
- ranks
(optional) integer vector, the ordering indices.
Details
An object of class featscreen
is a named list with eight elements:
method
the id of the used screening method
multi
the id of the used multi-response aggregation method
selection
the id of the used selection method
summary
a textual summary of the screening
n
the dimension of the feature space
features
the feature names
keep
the features to keep
ranks
the feature ranks
Functions to facilitate access to the data stored in a resampling
object are
available:
?getScreeningMethodId
: returns the screening method id?getMultiresponseAggregationMethodId
: returns the multi-response aggregation method id?getSelectionMethodId
: returns the selection method id?getSummary
: returns the textual summary of the screening?getFeatureDimensionality
: returns the dimension of the feature space?getFeatureNames
: returns the feature names?getScreenedFeatures
: returns the features to keep?getFeatureRanks
: returns the feature ranks
Other useful functions include:
print
: print a summary of thefeatscreen
object
Examples
#default
featscreen()
#featscreen object
featscreen(
method = 'cor.test',
selection = 'cutoff',
summary = '3 out of 5 features selected by a cutoff.',
n = 5,
keep = c(TRUE,FALSE,TRUE,FALSE,TRUE),
features = paste0("f", seq_len(5)),
ranks = c(1,5,3,4,2)
)
#>
#> 3 out of 5 features selected by a cutoff.
#>
#> Top 5 ranked features: f1, f5, f3, f4, f2
#>