Reverse Dependencies of lightgbm
The following projects have a declared dependency on lightgbm:
- recommendation-model-server — A real-time inference server
- recommenders — Recommenders - Python utilities for building recommendation systems
- responsibleai — SDK API to explain models, generate counterfactual examples, analyze causal effects and analyze errors in Machine Learning models.
- retrofit — AutoML, Forecasting, NLP, Image Classification, Feature Engineering, Model Evaluation, Model Interpretation, Fast Processing.
- rltrade-test — Easy to use Reinforcement Library for finance
- rumboost — Gradient Boosting Decision Trees for Random Utility Models
- run-models — Run all regression and classification models with its default parameters
- s2aff — Semantic Scholar's Affiliation Extraction: Link Your Raw Affiliations to ROR IDs
- s2cloudless — Sentinel Hub's cloud detector for Sentinel-2 imagery
- salesforce-merlion — Merlion: A Machine Learning Framework for Time Series Intelligence
- sapientml-core — A SapientML plugin of SapientMLGenerator
- scalarpy — Welcome to ScalarPy!
- scCloud — scRNA-Seq analysis tools that scale to millions of cells
- scEvoNet — Tool for generation [cell state - gene program] network
- scikit-digital-health — Python general purpose human motion inertial data processing package.
- scikit-physlearn — A machine learning library for regression.
- seaborn-analyzer — seaborn-analyzer: data visualization of regression, classification and distribution
- Seance — A Wrapper around MLForecast.
- secml-malware — no summary
- selective — feature selection library
- sensai — The Python library for sensible AI
- Sentinel-imgpackage — Sentinel satellite image module
- sfdc-merlion — Merlion: A Machine Learning Framework for Time Series Intelligence
- shap — A unified approach to explain the output of any machine learning model.
- shap-app — A comprehensive application for interpreting machine learning models using SHAP values
- shapash — Shapash is a Python library which aims to make machine learning interpretable and understandable by everyone.
- shaperone — Shaperone is a fork of the SHAP library, fixing open issues to improve usability.
- shortcutml — Machine learning baseline prototyping tools
- SIAC — A sensor invariant Atmospheric Correction (SIAC)
- sibyl-ai — Wrapper for SKLearn Pipeline with Auto ML features
- simager — Simple tools for auto classification and text preprocessing
- singletrader — a package for backtesting and factor analysis
- skforecast — Forecasting time series with scikit-learn regressors. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM, XGBoost, Ranger...).
- sklearn-utilities — Utilities for scikit-learn.
- sklearndf — Data frame support and feature traceability for `scikit-learn`.
- skops — A set of tools to push scikit-learn based models to and pull from Hugging Face Hub
- skt — SKT package
- sktmls — MLS SDK
- slim-trees — A python package for efficient pickling of ML models.
- smart-data-science — Personal side project to streamline the most common tasks of data science solutions in an efficient manner. This project is based on my experience as a lead data scientist in the industry and financial services sectors, where I have gained expertise in delivering effective data-driven insights and solutions
- snowflake-ml-python — The machine learning client library that is used for interacting with Snowflake to build machine learning solutions.
- social-net-img-classifier — no summary
- spaceopt — Hyperparameter optimization via gradient boosting regression
- sphynxml — no summary
- spike-explainability — Package containing several methods and functions for explaining and understanding machine learning models
- stableperovskites — Regression model package predicting the energy above hull of perovskite oxides.
- stepshifter3 — A general purpose stepshifting algorithm for tabular data, based on BaseEstimator.
- stglance — stglance is a small collection of streamlit widgets (for machine learning) that you can include in your streamlit app.
- stockait — Make your stock investment smarter, join StockAit!
- stringsifter — StringSifter is a machine learning tool that automatically ranks strings based on their relevance for malware analysis.
- swarmauri — This repository includes core interfaces, standard ABCs and concrete references, third party plugins, and experimental modules for the swarmaURI framework.
- tabgan — Applying GAN in tabular data generation for uneven distribution
- tablearn — tablearn: Learner for Tabular Data
- tabular-ml — This library wraps popular tabular regression/classification model enabling rapid evaluation and optimization.
- tabular-toolbox — A library of extension and helper modules for tabular data base on python's machine learning frameworks.
- tabular-trees — Package for making analysis on tree-based models easier
- task-substitution — Solve a different task which could help solve the main task
- TCAP — # TCAP
- teco-challenger-lib — no summary
- teddynote — datasets and tutorial package made and maintained by TeddyNote
- TezzAutoML — Just another AutoML library, but better and faster.
- TimeMurmur — Time series forecasting at scale with LightGBM
- titus-optimize — A package for optimizing placements of containers.
- toai — To AI helper library
- toai-mokahaiku — To AI helper library
- TPOT2 — Tree-based Pipeline Optimization Tool
- tql — description
- tql-Python — description
- tradescope — Tradescope - Crypto Trading Bot
- tradeX — Machine learning based crypto currency price prediction
- training-pipeline — no summary
- trainme — tune with optuna and model
- treeboost_autograd — treeboost_autograd
- treegrad — transfer parameters from lightgbm to differentiable decision trees!
- treemodel2sql — tree model transform to sql
- tsanalysis — Machine Learning library for time series analysis
- tsboost — Time series Framework
- TSEnsemble — A Python library for times series forecasting, which uses an ensemble of methods, including SARIMA and deep learning models
- tune-easy — tune-easy: A hyperparameter tuning tool, extremely easy to use.
- turnkeyml — TurnkeyML Tools and Models
- twinbooster — Python package for TwinBooster: Synergising Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery
- u8darts — A python library for easy manipulation and forecasting of time series.
- uncertainty-estimation-models — This is the main library for the uncertainty estimation project.
- upgini — Intelligent data search & enrichment for Machine Learning
- vai-utils — VAI utils
- vclean — vClean: Assessing the contamination of viral genomes
- vectice — Vectice Python library
- westData — A small example package
- wgcpy — Data analysis and PMML model framework!
- whyshift — A package of various specified distribution shift patterns of out-of-distributoin generalization problem on tabular data, and tools for diagnosing model performance are integrated.
- wideboost — Implements Wide Boosting functions for popular boosting packages
- wolta — Data Science Library
- wzyFunc — My Python Package
- xfeat — Feature Engineering & Exploration Library using GPUs and Optuna
- xorbits — Scalable Python data science, in an API compatible & lightning fast way.
- xtoy — get xtoyed predictions from raw data
- yaib — Yet Another ICU Benchmark is a holistic framework for the automation of the development of clinical prediction models on ICU data. Users can create custom datasets, cohorts, prediction tasks, endpoints, and models.
- Yikai-helper-funcs — Test nbdev for developing packages for self-resue
- yikit — This is my own tool kit.
- Yuan — description