add contributing and update

Author: JohnMount

.Rbuildignore

@@ -17,4 +17,4 @@
 ^extras$
 ^paper.md$
 ^paper.bib$
-
+^CONTRIBUTING.md$

CONTRIBUTING.md

@@ -0,0 +1,8 @@
+# Contributing
+
+The `vtreat` project is happy to examine good faith issues and pull requests [here](https://github.com/WinVector/vtreat).
+Also please feel free to email the maintaining contributor: John Mount `[email protected]`.
+
+Please understand we can not accept any code without having full rights and license assigned to Win-Vector LLC.
+
+Also we expect contributors to follow [GitHub Community Guidelines](https://help.github.com/articles/github-community-guidelines/).

README.Rmd

@@ -19,7 +19,7 @@ knitr::opts_chunk$set(
 
 [vtreat](http://winvector.github.io/vtreat/) is an [R](https://cran.r-project.org) data.frame
 processor/conditioner that prepares real-world data for
-predictive modeling in a statistically sound manner.  For more detail please see here: [arXiv:1611.09477 stat.AP](https://arxiv.org/abs/1611.09477).  There is also a series of articles recording the
+predictive modeling in a statistically sound manner.  For more detail please see here: [arXiv:1611.09477 stat.AP](https://arxiv.org/abs/1611.09477) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1173314.svg)](https://doi.org/10.5281/zenodo.1173314).  There is also a series of articles recording the
 evolution of `vtreat` including some tutorials [here](http://www.win-vector.com/blog/tag/vtreat/).
 
 ![](https://github.com/WinVector/vtreat/raw/master/tools/vtreat.png)

README.md

@@ -1,6 +1,6 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
-[vtreat](http://winvector.github.io/vtreat/) is an [R](https://cran.r-project.org) data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. For more detail please see here: [arXiv:1611.09477 stat.AP](https://arxiv.org/abs/1611.09477). There is also a series of articles recording the evolution of `vtreat` including some tutorials [here](http://www.win-vector.com/blog/tag/vtreat/).
+[vtreat](http://winvector.github.io/vtreat/) is an [R](https://cran.r-project.org) data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. For more detail please see here: [arXiv:1611.09477 stat.AP](https://arxiv.org/abs/1611.09477) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1173314.svg)](https://doi.org/10.5281/zenodo.1173314). There is also a series of articles recording the evolution of `vtreat` including some tutorials [here](http://www.win-vector.com/blog/tag/vtreat/).
 
 ![](https://github.com/WinVector/vtreat/raw/master/tools/vtreat.png)
 
@@ -145,8 +145,8 @@ treatmentsC <- designTreatmentsC(dTrainC,colnames(dTrainC),'y',TRUE,
                                  verbose=FALSE)
 print(treatmentsC$scoreFrame[,c('origName', 'varName', 'code', 'rsq', 'sig', 'extraModelDegrees')])
  #    origName   varName  code          rsq        sig extraModelDegrees
- #  1        x    x_catP  catP 1.559780e-01 0.22202097                 2
- #  2        x    x_catB  catB 1.142159e-05 0.99166241                 2
+ #  1        x    x_catP  catP 1.030137e-01 0.32099590                 2
+ #  2        x    x_catB  catB 1.125399e-05 0.99172381                 2
  #  3        z   z_clean clean 2.376018e-01 0.13176020                 0
  #  4        z   z_isBAD isBAD 2.960654e-01 0.09248399                 0
  #  5        x  x_lev_NA   lev 2.960654e-01 0.09248399                 0
@@ -192,9 +192,9 @@ treatmentsN = designTreatmentsN(dTrainN,colnames(dTrainN),'y',
                                 verbose=FALSE)
 print(treatmentsN$scoreFrame[,c('origName', 'varName', 'code', 'rsq', 'sig', 'extraModelDegrees')])
  #    origName   varName  code          rsq       sig extraModelDegrees
- #  1        x    x_catP  catP 1.764706e-01 0.3001022                 2
- #  2        x    x_catN  catN 3.533569e-03 0.8888051                 2
- #  3        x    x_catD  catD 3.743113e-01 0.1069707                 2
+ #  1        x    x_catP  catP 1.894619e-01 0.2810898                 2
+ #  2        x    x_catN  catN 2.532154e-01 0.2036653                 2
+ #  3        x    x_catD  catD 4.512437e-02 0.6135229                 2
  #  4        z   z_clean clean 2.880952e-01 0.1701892                 0
  #  5        z   z_isBAD isBAD 3.333333e-01 0.1339746                 0
  #  6        x  x_lev_NA   lev 3.333333e-01 0.1339746                 0