factor.encoder()
and numeric.encoder()
for
improved performance.weighted.rmse()
and its related functions into
a single, more versatile weighted.loss()
function.max.bars
to max.terms
, max.nrow
to max.rows
, etc.).weighted()
and its family functions.mid.extract()
and
mid.frames()
.color.theme()
to significantly enhance its
functionality and flexibility.numeric.encoder()
and
factor.encoder()
held an unnecessary reference to the
execution environment of interpret.default()
.interpret.formula()
and
factor.encoder()
to correctly support subset
and drop.unused.levels
arguments.get.yhat()
methods to ensure prediction outputs
always have the same length as the number of input observations.interpret.default()
.interpret.default()
that caused
inconsistency between “fitted.values” and “residuals”.mid.f()
(mid.effect()
)
to correctly handle vector recycling when an input’s length is 1.autoplot.mid.conditional()
to avoid redundant
evaluation of the “mid” object.k
) in interpret()
.color.theme()
for
easier theme specification.interpret.formula()
to resolve environment
issues related to stats::model.frame()
color.theme()
.midr.diverging
, midr.qualitative
and
midr.sequential
.interpret.formula()
to ensure the
evaluated formula
is correctly stored in the function
call.First release on CRAN.