textmodel_affinity-internal {quanteda.textmodels} | R Documentation |
Internal methods for textmodel_affinity
Description
Internal print and summary methods for derivative textmodel_affinity objects.
Usage
## S3 method for class 'influence.predict.textmodel_affinity'
print(x, n = 30, ...)
## S3 method for class 'influence.predict.textmodel_affinity'
summary(object, ...)
## S3 method for class 'summary.influence.predict.textmodel_affinity'
print(x, n = 30, ...)
Arguments
n |
how many coefficients to print before truncating |
Value
summary.influence.predict.textmodel_affinity()
returns a list
classes as summary.influence.predict.textmodel_affinity
that includes:
-
word
the feature name -
count
the total counts of each feature for which influence was computed -
mean
,median
,sd
,max
mean, median, standard deviation, and maximum values of influence for each feature, computed across classes -
direction
an integer vector of 1 or 2 indicating the class which the feature is influencing -
rate
a document by feature class sparse matrix of normalised influence measures -
count
a vector of counts of each non-zero feature in the input matrix -
rate
the median ofrate
frominfluence.predict.textmodel_affinity()
-
support
logical vector for each feature matching the same return frompredict.textmodel_affinity()
the mean, the standard deviation, the direction of the influence, the rate, and the support