younader/dnnr
The Python package of differential nearest neighbors regression (DNNR): Raising KNN-regression to levels of gradient boosting method. Build on-top of Numpy, Scikit-Learn, and Annoy.
When you need to predict a numerical outcome based on existing data, this tool helps you make more accurate predictions. It takes your input features and corresponding outcomes, and then generates predictions that are significantly more precise than basic nearest neighbor methods. This is for data scientists, machine learning engineers, or researchers who need to build high-performing regression models.
No commits in the last 6 months. Available on PyPI.
Use this if you are working with regression tasks and find that traditional K-Nearest Neighbors isn't accurate enough, but you want a method that still leverages data locality.
Not ideal if your primary goal is interpretability with simple linear relationships, or if you prefer gradient boosting methods and are already satisfied with their performance.
Stars
19
Forks
2
Language
Python
License
MIT
Category
Last pushed
Aug 04, 2022
Commits (30d)
0
Dependencies
5
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