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cat2cat_ml_run function to check the ml models
performance before cat2cat with ml option is run. Now, the
ml models are more transparent.ropensci standards, like CONTRIBUTING file and
testthat version 3.cat2cat_agg has updated cat_var argument
to two new ones, cat_var_old and
cat_var_new.master to main branch.freqs_df argument in the cat2cat
function is moved from data to mappings part, it is backward compatible.
Now it is consistent with the python cat2cat implementation.pkgcheck related fixes, like 80 chars per line.data and library calls style.cat2cat function.dummy_c2c to be backward compatible.cat_apply_freq function performance.ml argument in the dummy_c2c function
is redefined, shorter names for a simpler usage.cat2cat ml part is using direct
cat_var for target (for an update) dataset now, not the one
from the ml argument list.cat2cat validation, if the
trans table covers all needed levels.ml and data argument in
the cat2cat::cat2cat function, two additional arguments
each.prune_c2c scales the weights now, so still sum to one
for each subject.dummy_c2c to add a default
cat2cat columns to a data.frame.occupand occup_small datasets have 4
periods now.pkgdown reference.pkgdown website.deparse instead of deparse1.tinyverse world, even less dependencies.cat2cat function, the ml part is assuming
that categorical variable is always named “code”.cat2cat function.randomForest packages to
Suggests, they are delayed loaded now.occup_small dataset to pass checks in terms of
computation time of examples.cat2cat function - “knn”, “rf”,
“lda”.prune_c2c and cross_c2c to improve
processing of results.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.