NEWS for pdp package

Properly registered native routines and disabled symbol search.
Fixed a bug for gbm models using the multinomial distribution.
Refactored code to improve structure.
partial gained three new options: inv.link (experimental), ice, and center. The latter two have to do with constructing individual conditional expectation (ICE) curves and cetered ICE (c-ICE) curves. The inv.link option is for transforming predictions from models that can use non-Gaussian distibutions (e.g., glm, gbm, and xgboost). Note that these options were added for convenience and the same results (plus much more) can still be obtained using the flexible pred.fun argument. (#36).
plotPartial gained five new options: center, plot.pdp, pdp.col, pdp.lwd, and pdp.lty; see ?plotPartial for details.
Fixed default y-axis label for autoplot with two numeric predictors (#48).
Added CITATION file.
Better support for neuaral networks from the nnet package.
Fixed a bug for nnet::multinom models with binary response.

Added support for MASS::lda, MASS::qda, and mda::mars.
New arguments quantiles, probs, and trim.outliers in partial. These arguments make it easier to construct PDPs over the relevant range of a numeric predictor without having to specify pred.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 creating ggplot2 graphics from "partial" objects.

partial is now much faster with "gbm" object due to a call to gbm::plot.gbm whenever pred.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 to partial now refers to additional arguments to be passed onto stats::predict rather than plyr::aaply. For example, using partial with "gbm" objects will require specification of n.trees which can now simply be passed to partial via the ... argument.
Added the following arguments to partial: progress (plyr-based progress bars), parallel (plyr/foreach-based parallel execution), and paropts (list of additional arguments passed onto foreach when parallel = TRUE).
Various bug fixes.
partial now throws an informative error message when the pred.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) and pima (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`.

partial now makes sure each column of pred.grid has the correct class, levels, etc.
partial gained a new option, levelplot, which defaults to TRUE. The original option, contour, has changed and now specifies whether or not to add contour lines whenever levelplot = TRUE.