version bump and updated links

Author: topepo

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: parsnip
-Version: 0.1.4.9000
+Version: 0.1.5
 Title: A Common API to Modeling and Analysis Functions
 Description: A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', etc). 
 Authors@R: c(

NEWS.md

@@ -1,8 +1,15 @@
-# parsnip (development version)
+# parsnip 0.1.5
 
 * An RStudio add-in is availble that makes writing multiple `parsnip` model specifications to the source window. It can be accessed via the IDE addin menus or by calling `parsnip_addin()`.
 
-* For `xgboost` models, users can now pass `objective` to `set_engine("xgboost")`. 
+* For `xgboost` models, users can now pass `objective` to `set_engine("xgboost")`. (#403)
+
+* Changes to test for cases when CRAN cannot get `xgboost` to work on their Solaris configuration.
+
+* There is now an `augument()` method for fitted models. See `augment.model_fit`. (#401)
+
+* Column names for `x` are now required when `fit_xy()` is used. (#398)
+
 
 # parsnip 0.1.4
 

R/boost_tree.R

@@ -526,7 +526,7 @@ xgb_by_tree <- function(tree, object, new_data, type, ...) {
 #' @param weights An optional numeric vector of case weights. Note
 #'  that the data used for the case weights will not be used as a
 #'  splitting variable in the model (see
-#'  \url{http://www.rulequest.com/see5-win.html} for
+#'  \url{https://www.rulequest.com/see5-info.html} for
 #'  Quinlan's notes on case weights).
 #' @param minCases An integer for the smallest number of samples
 #'  that must be put in at least two of the splits.

README.Rmd

@@ -19,7 +19,7 @@ knitr::opts_chunk$set(
 [![R build status](https://github.com/tidymodels/parsnip/workflows/R-CMD-check/badge.svg)](https://github.com/tidymodels/parsnip/actions)
 [![Coverage status](https://codecov.io/gh/tidymodels/parsnip/branch/master/graph/badge.svg)](https://codecov.io/github/tidymodels/parsnip?branch=master)
 [![CRAN status](https://www.r-pkg.org/badges/version/parsnip)](https://CRAN.R-project.org/package=parsnip)
-[![Downloads](https://cranlogs.r-pkg.org/badges/parsnip)](https://cran.rstudio.com/package=parsnip)
+[![Downloads](https://cranlogs.r-pkg.org/badges/parsnip)](https://CRAN.R-project.org/package=parsnip)
 [![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
 <!-- badges: end -->
 
@@ -129,10 +129,10 @@ Data sets previously found in `parsnip` are now find in the `modeldata` package.
 
 This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
 
-- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://rstd.io/tidymodels-community).
+- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
 
 - If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/parsnip/issues).
 
-- Either way, learn how to create and share a [reprex](https://rstd.io/reprex) (a minimal, reproducible example), to clearly communicate about your code.
+- Either way, learn how to create and share a [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) (a minimal, reproducible example), to clearly communicate about your code.
 
 - Check out further details on [contributing guidelines for tidymodels packages](https://www.tidymodels.org/contribute/) and [how to get help](https://www.tidymodels.org/help/).

README.md

@@ -11,7 +11,7 @@ status](https://github.com/tidymodels/parsnip/workflows/R-CMD-check/badge.svg)](
 status](https://codecov.io/gh/tidymodels/parsnip/branch/master/graph/badge.svg)](https://codecov.io/github/tidymodels/parsnip?branch=master)
 [![CRAN
 status](https://www.r-pkg.org/badges/version/parsnip)](https://CRAN.R-project.org/package=parsnip)
-[![Downloads](https://cranlogs.r-pkg.org/badges/parsnip)](https://cran.rstudio.com/package=parsnip)
+[![Downloads](https://cranlogs.r-pkg.org/badges/parsnip)](https://CRAN.R-project.org/package=parsnip)
 [![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
 <!-- badges: end -->
 
@@ -78,19 +78,19 @@ between implementations.
 
 In this example:
 
-  - the **type** of model is “random forest”,
-  - the **mode** of the model is “regression” (as opposed to
+-   the **type** of model is “random forest”,
+-   the **mode** of the model is “regression” (as opposed to
     classification, etc), and
-  - the computational **engine** is the name of the R package.
+-   the computational **engine** is the name of the R package.
 
 The goals of parsnip are to:
 
-  - Separate the definition of a model from its evaluation.
-  - Decouple the model specification from the implementation (whether
+-   Separate the definition of a model from its evaluation.
+-   Decouple the model specification from the implementation (whether
     the implementation is in R, spark, or something else). For example,
     the user would call `rand_forest` instead of `ranger::ranger` or
     other specific packages.
-  - Harmonize argument names (e.g. `n.trees`, `ntrees`, `trees`) so that
+-   Harmonize argument names (e.g. `n.trees`, `ntrees`, `trees`) so that
     users only need to remember a single name. This will help *across*
     model types too so that `trees` will be the same argument across
     random forest as well as boosting or bagging.
@@ -141,7 +141,7 @@ rand_forest(mtry = 10, trees = 2000) %>%
   fit(mpg ~ ., data = mtcars)
 #> parsnip model object
 #> 
-#> Fit time:  71ms 
+#> Fit time:  83ms 
 #> Ranger result
 #> 
 #> Call:
@@ -171,17 +171,18 @@ This project is released with a [Contributor Code of
 Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
 By contributing to this project, you agree to abide by its terms.
 
-  - For questions and discussions about tidymodels packages, modeling,
+-   For questions and discussions about tidymodels packages, modeling,
     and machine learning, please [post on RStudio
-    Community](https://rstd.io/tidymodels-community).
+    Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
 
-  - If you think you have encountered a bug, please [submit an
+-   If you think you have encountered a bug, please [submit an
     issue](https://github.com/tidymodels/parsnip/issues).
 
-  - Either way, learn how to create and share a
-    [reprex](https://rstd.io/reprex) (a minimal, reproducible example),
-    to clearly communicate about your code.
+-   Either way, learn how to create and share a
+    [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html)
+    (a minimal, reproducible example), to clearly communicate about your
+    code.
 
-  - Check out further details on [contributing guidelines for tidymodels
+-   Check out further details on [contributing guidelines for tidymodels
     packages](https://www.tidymodels.org/contribute/) and [how to get
     help](https://www.tidymodels.org/help/).