add feature weights (w-k prototypes) #200
Open
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
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Outdated suggestions cannot be applied.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.
Based on proposed approach by Çörekci, Osman, and Ayla Saylı. "A New Clustering Algorithm of Hybrid Data According to Weights of Attributes." Avrupa Bilim ve Teknoloji Dergisi 5.9 (2016): 28-37.
Implemented feature adds feature weights by passing a weight argument per categorical and numerical feature. This weight is used by both default similarity functions (euclidian for numerical and matching for categorical). Assertions checking for correctly passed weights are added under init and fit methods.
Pending: include integration tests