order()
on data.frame
objectsexplain()
will now pass ...
on to the relevant predict()
method (#150)explain.data.frame()
gains a gower_pow
argument to modify the calculated
gower distance before use by raising it to the power of the given value (#158)lime()
now warns when quantile binning is not feasible and uses standard
binning instead (#154)lambda
value in the local model fit to match the one used in the
Python version according to the relationship given here:
https://stats.stackexchange.com/a/270705parsnip
and ranger
preprocess
argument to lime.data.frame
to keep it in line with the
other types. Use it to transform your data.frame into a new input that your
model expects after permutationsmagick
is now only in suggest to cut down on heavy hard dependenciesexplain
now returns a tbl_df
so you get pretty printing if you have
tibble
loadedplot_features
now has a cases
argument for subsetting the data before
plottingplot_image_explanation
(#35)keras
packageas_classifier()
and as_regressor()
for ad-hoc specification of the
model type in case the heuristic implemented in lime
doesn't hold.
as_classifier()
also lets you add/overwrite the class labels.gower
as the new default similarity measure for tabular databin_continuous = FALSE
the default behavior is now to sample from a
kernel density estimation rather than assume a normal distribution.plot_explanations()
(#60)plot_text_explanation()
with better formatting and scrolling
support for many explanationsNEWS.md
file to track changes to the package.NA
values (#8) plot_features()
(#38)h2o
(@mdancho84) (#40)NA
values (#45)Date
and POSIXt
columns. They will be kept constant during
permutations so that lime
will explain the model behaviour at the given
timepoint based on the remaining features (#39).plot_explanations()
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