Reverse Dependencies of lightgbm
The following projects have a declared dependency on lightgbm:
- mlshell — Ml framework.
- mlsuite — The traditional machine learning analysis based on sklearn package
- mmfunctions — Helper package to be used in conjunction with the Maximo Asset Manager pipeline
- model-monitoring — Model Monitoring
- modelLab — A lib for automating model training process of choosing best model that works for you data
- morai — A mortality viewer
- ms1searchpy — A proteomics search engine for LC-MS1 spectra.
- MultiTrain — MultiTrain allows you to train multiple machine learning algorithms on a dataset all at once to determine the best for that particular use case
- musket-core — The core of Musket ML
- myylearn — An General Automated Machine Learning Framework
- namedivider-python — A tool for dividing the Japanese full name into a family name and a given name.
- naszilla — python framework for NAS algorithms on benchmark search spaces
- nclick — Code for Laziness.
- neptune-lightgbm — Neptune.ai LightGBM integration library
- nessie — Annotation error detection and correction
- nestedhyperboost — A wrapper for conducting Nested Cross-Validation with Bayesian Hyper-Parameter Optimized Gradient Boosting
- neurodecode — Real-time brain signal decoding framework
- nexora — This is an ML project in order to automate ML processes
- nextstep — USEP price prediction
- nlp4ml — Python NLP wrapper
- nullpom — Library to easily run Null Importances.
- nyaggle — Code for Kaggle and Offline Competitions.
- octopus-ml — A collection of handy ML and data validation tools
- omlt — OMLT is a Python package for representing machine learning models (such as neural networks) within the Pyomo optimization environment.
- onnx-extended — Extends the list of supported operators in onnx reference implementation and onnxruntime, or implements faster versions in C++.
- openbox — Efficient and generalized blackbox optimization (BBO) system
- openfe — OpenFE: automated feature generation with expert-level performance
- openstef — Open short term energy forecaster
- openstf — Open short term forcasting
- OptGBM — Optuna + LightGBM \= OptGBM
- optuna — A hyperparameter optimization framework
- optuna-integration — Integration libraries of Optuna.
- oracle-ads — Oracle Accelerated Data Science SDK
- oracle-automlx — Automated Machine Learning with Explainability
- ordinalgbt — A library to build Gradient boosted trees for ordinal labels
- oscar-test0629 — For testing.
- pandaslearn — `pandaslearn` is a small wrapper on top of `scikit-learn` to automate common modeling tasks.
- paragrid — Simple parallelized grid search to find the best hyperparameters
- PatryksAutoAI — Auto_AI_patryk
- pegasuspy — Pegasus is a Python package for analyzing sc/snRNA-seq data of millions of cells
- penguin-libraries — Easy and useful libraries.
- perlib — Deep learning, Machine learning and Statistical learning for humans.
- personalization — An end-to-end machine learning pipeline to train ml model and deploy it to realtime inference endpoint
- pgml-extension — Simple machine learning in PostgreSQL.
- phenopy — Phenotype comparison scoring by semantic similarity.
- PiML — A low-code interpretable machine learning toolbox in Python.
- PipelineTS — One-stop time series analysis tool, supporting time series data preprocessing, feature engineering, model training, model evaluation, model prediction, etc. Based on spinesTS and darts.
- pitci — Prediction intervals for trees using conformal intervals - pitci
- player-performance-ratings — Match Predictions based on Player Ratings
- pnow — A restful client library, designed to access predictnow restful API.
- pou-shap — A unified approach to explain the output of any machine learning model.
- pre-ai-python — Microsoft AI Python Package
- pre-reco-utils — Recommender System Utilities
- predictnow — A restful client library, designed to access predictnow restful API.
- predictnow-api — A restful client library, designed to access predictnow restful API.
- predictnow-client — A restful client library, designed to access predictnow restful api.
- prenigma-automl — prenigma_automl - An open source, low-code machine learning library.
- prenigmaautoml — prenigma_automl - An open source, low-code machine learning library.
- preprocess1 — no summary
- prettymetrics — One place metrics for various ML regression and classification algorithms
- prevision-quantum-nn — Prevision Automating Quantum Neural Networks Applications
- probatus — Validation of regression & classifiers and data used to develop them
- prolothar-rule-mining — algorithms for prediction and rule mining on event sequences
- pspso — pspso is a python package for selecting machine learning algorithms parameters.
- py-automl-lib — Python package for automated hyperparameter-optimization of common machine-learning algorithms
- pyautomlib — Creating machine learning and preprocessing models
- pybirds — Business Intelligence Risk Data Science
- pycaML — Python Comparative Analysis for Machine Learning
- pycaret — PyCaret - An open source, low-code machine learning library in Python.
- pycaret-nightly — Nightly version of PyCaret - An open source, low-code machine learning library in Python.
- pycaret-ts-alpha — PyCaret - An open source, low-code machine learning library in Python.
- pyDSlib — General utilities to streamline data science and machine learning routines in python
- pyemits — python package for easy manipulation on time series data for quick insight
- pyepal — PyePAL implemented the epsilon-PAL active learning algorithm
- pymlpipe — PyMLpipe is a Python library for ease Machine Learning Model monitering and Deployment.
- pymlup — MLup framework, fast ml to production, easy to learn, easy to use.
- pymlx — Yet another machine learning framework
- pyoats — Quick and Easy Time Series Outlier Detection
- pyqlib — A Quantitative-research Platform
- pyRealEstate — package to assist with data analytics in real estate
- pyrecdp — A data processing bundle for spark based recommender system operations
- pyserini-install — A Python toolkit for reproducible information retrieval research with sparse and dense representations
- PySRAG — This Python package provides tools for analyzing and processing data related to Severe Acute Respiratory Syndrome (SARS) and other respiratory viruses. It includes functions for data preprocessing, feature engineering, and training Gradient Boosting Models (GBMs) for binary or multiclass classification.
- pythie-serving — A GRPC server to serve model types using tensorflow-serving .proto services
- python-allib — A typed Active Learning Library
- python-iArt — iArt: A Generalized Framework for Imputation-Assisted Randomization Tests
- python-sumo — **sumo** is a command-line tool to identify molecular subtypes in multi-omics datasets. It implements a novel nonnegative matrix factorization (NMF) algorithm to identify groups of samples that share molecular signatures, and provides additional modules to evaluate such assignments and identify features that drive the classification.
- python-vivid — Support Tools for Machine Learning VIVIDLY
- pythonqlib — A Quantitative-research Platform
- pytorch-frame — Tabular Deep Learning Library for PyTorch
- quartic-sdk — QuarticSDK is the SDK package which exposes the APIs to the user
- quickerml — Machine learning toolkit to find the best starting model for your project
- rai-test-utils — Common basic test utilities used across various RAI tools
- raitracker — Responsible AI Toolbox Tracker
- raiwidgets — Interactive visualizations to assess fairness, explain models, generate counterfactual examples, analyze causal effects and analyze errors in Machine Learning models.
- ranktreeEnsemble — Fast computing an ensemble of rank-based trees via boosting or random forest on binary and multi-class problems. It converts continuous gene expression profiles into ranked gene pairs, for which the variable importance indices are computed and adopted for dimension reduction.
- rapidgbm — RapidGBM is a powerful Python package designed to streamline the process of tuning LightGBM models using the optimization framework Optuna.
- rapidoml — RapidoML is a simple Automated Machine Learning (AutoML) library
- rapidpredict — rapid predict is a python package to simplifies the process of fitting and evaluating multiple machine learning models on a dataset.
- RealEstate-package — МЛ-модель, предсказывающая стоимость недвижимости по её параметрам.