lsorber/neo-ls-svm
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
This project helps data analysts and machine learning practitioners create predictive models for classification and regression tasks. You input your labeled datasets (like customer churn records or housing prices), and it outputs a model that can predict outcomes, along with calibrated prediction intervals and quantiles. This is for professionals who need accurate predictions and a clear understanding of prediction uncertainty, especially when dealing with larger datasets.
No commits in the last 6 months. Available on PyPI.
Use this if you need to build robust classification or regression models with reliable uncertainty estimates and efficient performance on moderately large datasets, without extensive hyperparameter tuning.
Not ideal if your primary goal is to interpret the specific coefficients of a linear model or if you are working with extremely small datasets where simpler models might suffice.
Stars
34
Forks
3
Language
Python
License
MIT
Category
Last pushed
Apr 01, 2024
Commits (30d)
0
Dependencies
4
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