Merge pull request #535 from tidymodels/0-1-7-RC

0.1.7 release candidate

Author: topepo

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 0.1.6.9000
+Version: 0.1.7
 Authors@R: 
     c(person(given = "Max",
              family = "Kuhn",
@@ -45,7 +45,7 @@ Imports:
 Suggests: 
     C50,
     covr,
-    dials (>= 0.0.9.9000),
+    dials,
     earth,
     keras,
     kernlab,
@@ -67,8 +67,6 @@ Suggests:
     xgboost
 VignetteBuilder: 
     knitr
-Remotes: 
-    tidymodels/dials
 ByteCompile: true
 Config/Needs/website:C50, earth, glmnet, keras, kernlab, kknn, LiblineaR,
     mgcv, nnet, parsnip, randomForest, ranger, rpart, rstanarm, tidymodels,

NEWS.md

@@ -1,4 +1,4 @@
-# parsnip (development version)
+# parsnip 0.1.7
 
 ## Model Specification Changes
 

README.md

@@ -79,19 +79,19 @@ 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.
@@ -142,7 +142,7 @@ rand_forest(mtry = 10, trees = 2000) %>%
   fit(mpg ~ ., data = mtcars)
 #> parsnip model object
 #> 
-#> Fit time:  71ms 
+#> Fit time:  73ms 
 #> Ranger result
 #> 
 #> Call:
@@ -172,18 +172,18 @@ 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://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
+-   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/).

man-roxygen/spec-references.R

@@ -1 +1 @@
-#' @references \url{https://www.tidymodels.org}, [_Tidy Models with R_](https://tmwr.org)
+#' @references \url{https://www.tidymodels.org}, [_Tidy Models with R_](https://www.tmwr.org/)