perpetual-ml / perpetual
A self-generalizing gradient boosting machine which doesn't need hyperparameter optimization
☆355Updated last month
Alternatives and similar repositories for perpetual:
Users that are interested in perpetual are comparing it to the libraries listed below
- Polars extension for general data science use cases☆417Updated this week
- Plugins/extension for Polars☆273Updated last month
- Time series analysis for Rust, with bindings to Python and Javascript☆231Updated this week
- How you (yes, you!) can write a Polars Plugin☆122Updated last week
- A lightweight gradient boosted decision tree package.☆67Updated 7 months ago
- Polars least squares extension - enables fast linear model polar expressions☆127Updated 3 months ago
- Lightweight and extensible compatibility layer between dataframe libraries!☆759Updated this week
- Polars plugin offering eXtra stuff for DateTimes☆191Updated last month
- Simplifying conditional Polars Expressions with Python 🐍 🐻❄️☆104Updated last week
- Visualize decision trees in Python☆467Updated last month
- ☆114Updated 10 months ago
- The repository to showcase the best framework for tabular data - the Awesome CatBoost☆205Updated this week
- Polars plugin for pairwise distance functions☆57Updated 3 weeks ago
- LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.☆161Updated this week
- Project template for Polars Plugins☆71Updated last week
- A probabalistic ML tool for science☆111Updated last month
- Cookbook to build Rust Candle models☆77Updated last year