The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Top 16 regression-model Open-Source Projects
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood. (by uber)
-
-
-
-
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
notebooks
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers. (by differential-machine-learning)
-
llm4regression
Examining how large language models (LLMs) perform across various synthetic regression tasks when given (input, output) examples in their context, without any parameter update
-
HockeyPenaltyPrediction
A machine learning experiment to predict NHL penalty minutes based on matchups using Azure Machine Learning and automated machine learning
-
terry_stops_analysis
This project analyses Terry Stops recorded by officers of the Seattle Police Department and see which key features of a terry stop lead to an arrest.
-
ols_regression
OLS regression with possibility of controlling for fixed effects and robust standard errors
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: 80% faster, 50% less memory, 0% loss of accuracy Llama finetuning | news.ycombinator.com | 2023-12-01Good point - the main issue is we encountered this exact issue with our old package Hyperlearn (https://github.com/danielhanchen/hyperlearn).
I OSSed all the code to the community - I'm actually an extremely open person and I love contributing to the OSS community.
The issue was the package got gobbled up by other startups and big tech companies with no credit - I didn't want any cash from it, but it stung and hurt really bad hearing other startups and companies claim it was them who made it faster, whilst it was actually my work. It hurt really bad - as an OSS person, I don't want money, but just some recognition for the work.
I also used to accept and help everyone with their writing their startup's software, but I never got paid or even any thanks - sadly I didn't expect the world to be such a hostile place.
So after a sad awakening, I decided with my brother instead of OSSing everything, we would first OSS something which is still very good - 5X faster training is already very reasonable.
I'm all open to other suggestions on how we should approach this though! There are no evil intentions - in fact I insisted we OSS EVERYTHING even the 30x faster algos, but after a level headed discussion with my brother - we still have to pay life expenses no?
If you have other ways we can go about this - I'm all ears!! We're literally making stuff up as we go along!
Project mention: Bayesian Structural Equation Modeling using blavaan | news.ycombinator.com | 2023-11-09It is much less challenging with Bambi[1] and brms[2].
[1] https://bambinos.github.io/bambi/
Project mention: LLM Is a Capable Regressor When Given In-Context Examples | news.ycombinator.com | 2024-04-13If you're interested in exploring other metrics, the output of the models and code examples for how to read them are available at: https://github.com/robertvacareanu/llm4regression/tree/main/...
For example:
> In fact, polynomial interpolants in Chebyshev points are problem-free when evaluated by the barycentric interpolation formula. They have teh same behavior as discrete Fourier series for period functions, whose reliability nobody worries about. The introduction of splines is a red herring: the true advantage of splines is not that they converge where polynomials fail to do so, but that they are more easility adapted to irregular point distributions and more localized.
You can see also the software package https://www.chebfun.org/ for Chebyshev interpolations with Matlap and https://github.com/rnburn/bbai for interpolation Chebyshev interpolations of arbitrary dimension functions with sparse grids for Python.
Project mention: Show HN: Okkam – find best-fit polynomial for arbitrary data using a GA | news.ycombinator.com | 2024-04-20
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
regression-models related posts
- Bayesian Structural Equation Modeling using blavaan
- Cubic Spline Interpolation
- Ask HN: What Are You Learning?
- [P] Deterministic Objective Bayesian Analysis for Spatial Models
- Show HN: Deterministic objective Bayesian inference for spatial models [pdf]
- how can I build a regression model which is penalised for moving away from an assumed set of coefficients?
- [P] Fit Logistic Regression with Jeffreys Prior
-
A note from our sponsor - WorkOS
workos.com | 24 Apr 2024
Index
What are some of the best open-source regression-model projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | statsmodels | 9,534 |
| 2 | ggstatsplot | 1,919 |
| 3 | orbit | 1,799 |
| 4 | hyperlearn | 1,510 |
| 5 | easystats | 1,019 |
| 6 | bambi | 1,009 |
| 7 | Morpheus | 236 |
| 8 | notebooks | 132 |
| 9 | llm4regression | 88 |
| 10 | bbai | 41 |
| 11 | MathAI | 30 |
| 12 | HockeyPenaltyPrediction | 1 |
| 13 | okkam | 0 |
| 14 | HoRM | 0 |
| 15 | terry_stops_analysis | 0 |
| 16 | ols_regression | 0 |
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com