- Properly registered native routines and disabled symbol search.
- Fixed bug for
gbm
objects with the multinomial distribution. - Refactored code to improve structure.
partial
gained three new options:inv.link
(experimental),ice
, andcenter
. The latter two have to do with constructing individual conditional expectation (ICE) curves and cetered ICE (c-ICE) curves. Theinv.link
option is for transforming predictions from models that can use non-Gaussian distibutions (e.g.,glm
,gbm
, andxgboost
). Note that these options were added for convenience and the same results (plus much more) can still be obtained using the flexiblepred.fun
argument. (#36).plotPartial
gained five new options:center
,plot.pdp
,pdp.col
,pdp.lwd
, andpdp.lty
; see?plotPartial
for details.- Fixed default y-axis label for
autoplot
with two numeric predictors (#48).
- Fixed minor pandoc conversion issue with
README.md
. - Added subdirectory called
tools
to hold figures forREADME.md
.
- Registered native routines and disabled symbol search.
- Added support for
MASS::lda
,MASS::qda
, andmda::mars
. - New arguments
quantiles
,probs
, andtrim.outliers
inpartial
. These arguments make it easier to construct PDPs over the relevant range of a numeric predictor without having to specifypred.grid
, especially when outliers are present in the predictors (which can distort the plotted relationship). - The
train
argument can now accept matrices; in particular, object of class"matrix"
or"dgCMatrix"
. This is useful, for example, when working with XGBoost models (i.e., objects of class"xgb.Booster"
). - New logical argument
prob
indicating whether or not partial dependence values for classification problems should be returned on the original probability scale, rather than the centered logit; details for the centered logit can be found on page 370 in the second edition of The Elements of Statistical Learning. - Fixed some typos in
NEWS.md
. - New function
autoplot
for automatically creatingggplot2
graphics from"partial"
objects.
partial
is now much faster with"gbm"
object due to a call togbm::plot.gbm
wheneverpred.grid
is not explicitly given by the user. (gbm::plot.gbm
exploits a computational shortcut that does not involve any passes over the training data.)- New (experimental) function
topPredictors
for extracting the names of the most "important" predictors. This should make it one step easier (in most cases) to construct PDPs for the most "important"" features in a fitted model. - A new argument,
pred.fun
, allows the user to supply their own prediction function. Hence, it is possible to obtain PDPs based on the median, rather than the mean. It is also possible to obtain PDPs for classification problems on the probability scale. See?partial
for examples. - Minor bug fixes and documentation tweaks.
- The
...
argument in the call topartial
now refers to additional arguments to be passed ontostats::predict
rather thanplyr::aaply
. For example, usingpartial
with"gbm"
objects will require specification ofn.trees
which can now simply be passed topartial
via the...
argument. - Added the following arguments to
partial
:progress
(plyr
-based progress bars),parallel
(plyr
/foreach
-based parallel execution), andparopts
(list of additional arguments passed ontoforeach
whenparallel = TRUE
). - Various bug fixes.
partial
now throws an informative error message when thepred.grid
argument refers to predictors not in the original training data.- The column name for the predicted value has been changed from
"y"
to"yhat"
.
randomForest
is no longer imported.- Added support for the
caret
package (i.e., objects of class"train"
). - Added example data sets:
boston
(corrected Boston housing data) andpima
(corrected Pima Indians diabetes data). - Fixed error that sometimes occurred when
chull = TRUE
causing the convex hull to not be computed. - Refactored
plotPartial
to be more modular. - Added
gbm
support for most non-"binomial"
families`.
randomForest
is now imported.- Added examples.
- Fixed a non canonical CRAN URL in the README file.
partial
now makes sure each column ofpred.grid
has the correct class, levels, etc.partial
gained a new option,levelplot
, which defaults toTRUE
. The original option,contour
, has changed and now specifies whether or not to add contour lines wheneverlevelplot = TRUE
.
- Fixed a number of URLs.
- More thorough documentation.
- Fixed a couple of URLs and typos.
- Added more thorough documentation.
- Added support for C5.0, Cubist, nonlinear least squares, and XGBoost models.
- Initial release.