https://github.com/bigmlcom/bigml-r
Simple R bindings for BigML.io
https://github.com/bigmlcom/bigml-r
Last synced: 3 months ago
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Simple R bindings for BigML.io
- Host: GitHub
- URL: https://github.com/bigmlcom/bigml-r
- Owner: bigmlcom
- Created: 2012-05-01T21:23:53.000Z (over 13 years ago)
- Default Branch: master
- Last Pushed: 2015-05-27T01:03:17.000Z (over 10 years ago)
- Last Synced: 2024-04-16T10:58:59.706Z (over 1 year ago)
- Language: R
- Size: 171 KB
- Stars: 8
- Watchers: 23
- Forks: 14
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
This repo contains the source code used to generate the BigML api
bindings for R.
Please, report problems and bugs to our
[BigML.io issue tracker](https://github.com/bigmlcom/io/issues)
Discussions about the different bindings take place in the general
[BigML mailing list](http://groups.google.com/group/bigml). Or join us
in our [Campfire chatroom](https://bigmlinc.campfirenow.com/f20a0)
# Build #
There is a small bundle.R script that will build a CRAN-ready bundle.
[Roxygen2](http://cran.r-project.org/web/packages/roxygen2/index.html)
is necessary for building the package documentation. Simply run the
script in R while in the project directory.
# Tests #
There is a small unit test script called run_tests.R.
These tests compare the class structure of bigml responses to the
expected class structure (in JSON form). It will also check for
specific known responses (e.g., A particular response for a prediction
request on a model trained from the iris dataset). Simply evaluate the
code in run_tests.R in the project root in order to run the tests.
It requires the
[testthat](http://cran.r-project.org/web/packages/testthat/index.html)
library by Hadley Wickham. Simply run the script in R while in the
project directory by executing "R -f bundle.R".
It is necessary to run setCredentials() beforehand, or to set
`BIGML_USERNAME` and `BIGML_API_KEY` appropriately in your .Renviron
file.
There are some small utilities (misc.R) that make it easier to
manipulate the complex datastructures returned by R and the bigml API.