Support Support Vector Machine models #31
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Codecov Report
@@ Coverage Diff @@
## master #31 +/- ##
==========================================
Coverage 100.00% 100.00%
==========================================
Files 13 16 +3
Lines 735 956 +221
==========================================
+ Hits 735 956 +221
Continue to review full report at Codecov.
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR adds support for Support Vector Machines. Radial-basis, linear, polynomial and sigmoid kernels are all supported. Categorical support is implemented by one hot encoding features, just like done for linear models. Results are consistent with sklearn2pmml models, as the integration tests reflect. PMML models from R with
svmfrom thee1071library have embedded feature scaling, for which we will add support in a follow-up PR shortly.