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author | Christoph Helma <helma@in-silico.ch> | 2017-01-11 08:24:23 +0100 |
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committer | Christoph Helma <helma@in-silico.ch> | 2017-01-11 08:24:23 +0100 |
commit | ed0d7edee4ac9831b58a01555de8bdba3534495e (patch) | |
tree | 6eae2f15554e6780576eac4bdd79a6a8422977ba /README.md | |
parent | b5d6446f058916d018139948002b6e9d1162d4fe (diff) |
model documentation updated
Diffstat (limited to 'README.md')
-rw-r--r-- | README.md | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -87,7 +87,7 @@ Execute the following commands either from an interactive Ruby shell or a Ruby s #### Experiment with other datasets, endpoints and algorithms - You can pass training_dataset, prediction_feature and algorithms parameters to the `Model::Validation.create_from_enanomapper` command. The [API documentation](http://rdoc.info/gems/lazar) provides detailed instructions. + You can pass training_dataset, prediction_feature and algorithms parameters to the `Model::Validation.create_from_enanomapper` command. The [API documentation](http://rdoc.info/gems/lazar) provides detailed instructions. Detailed documentation and validation results can be found in this [publication](https://github.com/enanomapper/nano-lazar-paper/blob/master/nano-lazar.pdf). Documentation ------------- |