Implementation of a regression tree in python #152
Merged
Conversation
This file contains hidden or 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
I've implemented a basic decision tree in python as an example of how they work. Although the class I've created only works on one dimensional data sets, the reader should be able to generalize it to higher dimensions should they need to.
I added these return statements so that invalid inputs or valid end cases would no longer continue running through the rest of the function.
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Outdated suggestions cannot be applied.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.
I've implemented a basic decision tree in python as an example of how they work. Although the class I've created only works on one dimensional data sets, the reader should be able to generalize it to higher dimensions or non-continuous labels should they need to.
I believe that decision trees should be in this repository because they're fundamental in any machine learning course and are important in the field.