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Updated all examples to use the new dataset,
yields
.
Topic based vignettes are now available.
Added a new dataset yields
that may be useful for
testing purposes.
Fixed issues with knitr
causing failing
builds.
Updated docs with newer examples.
fit_models
to support model fitting for
several variables for several model types.Major additions
extract_model_info now supports
glmerMod
and glmmTMB
get_this now works with numeric input and also
supports data.frame
objects.
fit_models extends fit_model by building many models at once.
Other changes
get_stats
now drops columns via a vector and not
“non_numeric” as previously.
Metrics from multi_model_1
are now more informative
with the metric and method wrapped in the naming of the result.
df
was renamed as old_data
in
multi_model_1
, newdata
to
new_data
.
plot_corr
now directly accepts
data.frame
objects. Arguments like
round_values
have also been dropped.
Fixed DOI to Max Kuhn’s paper
Refactored get_mode
to be tidy
compliant.
The argument valid
was dropped in
multi_model_1
.
get_all
was dropped in
select_percentile
.
select_col
, select_percentile
,
row_mean_na
will be removed in the next release.
row_mean_na
is now defunct. Use
na_replace
instead.
na_replace
no longer allows using functions such as
mean
,min
, etc. These have been reimplemented
in the package mde
modeleR
is now defunct. Use fit_model
instead.
get_this
no longer accepts non quoted character
strings.
Better coverage and code tests
Fixes paper citation
New functions
plot_corr
has been added to allow plotting of
correlation matrices produced by get_var_corr_
.
na_replace_grouped
extends na_replace
by allowing replacement of missing values(NA
s) by
group.
add_model_predictions
allows addition of predicted
values to a data set.
add_model_residuals
is an easy to use and
dplyr
compatible wrapper that allows addition of residuals
to a data set.
extract_model_info
allows easy extraction of common
model attributes such as p values, residuals, coefficients, etc as per
the specific model type. It supports extraction of multiple
attributes.
multi_model_2
allows fitting and predicting in one
function. It is similar to multi_model_1
except it does not
require metrics.
Major Changes
modeleR
has been replaced with
fit_model
which is an easier to remember name. Usage
remains the same.
fit_model
no longer allows direct addition of
predictions. Use add_model_predictions
to achieve the
same.
na_replace
has been extended to allow for user
defined values.
rowdiff
now accepts replacement of the calculation
induced NA
s. It does so by using
na_replace
.
get_var_corr_
now supports using only a subset of
the data.
Helper functions are no longer exported.
get_data_Stats
is now aliased with
get_stats
for ease.
get_var_corr
no longer has the get_all
argument. Instead, users can provide an option other_vars
vector of subset columns. drop_columns
has also been
changed from boolean
to a character vector.
Minor bug fixes with respect to the vignette.
Major Changes
Additions
agg_by_group
is a new function that manipulates
grouped data. It is fast and robust for many kinds of
functions.
rowdiff
is another new function that enable one to
find differences between rows in a data.frame object. `
get_var_corr
provides a user-friendly way to find
correlations between data.
get_var_corr_
provides a user-friendly way to find
combination-wise correlations. It is relatively fast depending on how
big one’s data is and/or machine specifications.
get_this
is an easy to use helper function to get
metrics,predictions, etc. Currently supports lists and data.frame
objects.
modeleR
and row_mean_na
were
removed.
Major Modifications
get_data_Stats
now supports removal of missing data
as well as using only numeric data.
modeleR
has been fixed to handle new data as
expected. It also now supports glm.
multi_model_1
now supports either validation or
working with new data.
row_mean_na
has been replaced with na_replace which
is more robust. row_mean_na
will be removed in future
versions.
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.