Reverse Dependencies of imblearn

The following projects have a declared dependency on imblearn:

• allcools — Toolkit for single-cell DNA methylome and multiomic data analysis.
• anoapycore — Anoa Python Core Package
• araucanaxai — A novel approach for generating explanations of the predictions of a generic ML model
• astro-ghost — A package to associate transients with host galaxies, and a database of 16k SNe-host galaxies in PS1.
• astro-ghost-ysepz — Database of supernovae and the photometric and spectroscopic properties of their host galaxies
• auto-aiml — Creates a best predictive regression/classification model
• auto-machine-learning — This is an python Library for AutoML which works for prediction and classification tasks.
• AutoBrewML — With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
• AutomatedCleaning — Automated Data Cleaning Library
• autoneuro-pypi — Template python package
• baseline-optimal — no summary
• boexplain — BOExplain
• brain-pred-toolbox — The Brain Predictability toolbox (BPt) is a Python based machine learning library designed to work with a range of neuroimaging data. Warning: Not actively maintained as of 11/30/22.
• buildml — Let's make building machine learning models the complex way, easy.
• classification-analysis — This library is to monitor your model during the training process and track the metrics to find the best model
• contentai-activity-classifier — ContentAI Activity Classification Service
• credit-scoring-model — Credit scoring model package.
• creditcard-customers-churn-gbm-model — Example Credit Card Customer Churn dataset Gradient Boosting model package from Train In Data.
• CS-MINI-2024Z-AutoML — An AutoML project with various machine learning capabilities.
• cumulative-cost-boosting — Parameter free cost-sensitive adaptive boosting
• cuoco — Cuoco is a tool for automatic data preprocessing. Cuoco comes from Italy, means chef.
• data-science-common-core — Data Science Common Core
• Data42 — Library specializing in data cleaning, visualization and prediction
• datalibs — A bunch of functions useful for data science (mostly wrappers around other libraries)
• deepehrgraph — no summary
• deepmol — DeepMol: a python-based machine and deep learning framework for drug discovery
• dl-data-analysis — no summary
• dnneasyensemble — a package for easyensemble whose basemodel is dnn
• dpone-datagenie — Synthetic DataGen is a powerful online library designed to generate synthetic data sets for various use cases. It leverages advanced algorithms and customizable parameters to create realistic data that closely mimics real-world data while ensuring privacy and security.
• ds-core-sanpier — A package to automize some of the steps before modeling and in the modeling stage
• easycreditscoring — Simple library combining efficient credit scoring ML methods
• edgaro — Explainable imbalanceD learninG compARatOr
• eeg-ml-pipeline — A Python package for EEG machine learning analysis, classification, and visualization.
• EtaML — An automated machine learning platform with a focus on explainability
• evoml — EvoML Framework
• feat-engine — no summary
• FeatureFlex — An AutoML project with various machine learning capabilities.
• financial-model-taiwan — A financial model package trained on data from Taiwan fiscal year 1999-2009
• foggy — foggy is a python package for using a CNN to predict fog at airports
• funky-ml — Automated ML by GD-Singh
• gdprCrawlerTest19 — GDPR document crawler
• gdprCrawlerTest20 — GDPR document crawler
• Gedi — Generating Event Data with Intentional Features for Benchmarking Process Mining
• genmrmr — Algorithm that uses genetic and MRMR for feature selection
• geochemistrypi — A highly automated machine learning Python framework dedicating to build up MLOps level 1 software product for data-driven geochemistry discovery
• gps-ms — A self-denoising and machine-learning based statistical generalized peakgroup scoring algorithm for SWATH-MS data
• gumly — Gumly
• iljicevs-ml — Library implementation of the Iljiceva model.
• ImbBag — Package contains a collection of bagging ensemble algorithms for imbalanced data
• IREX — no summary
• ITMO-FS — Python Feature Selection library from ITMO University.
• JasonUtils — Jason's Utils
• JO-AutoMl-Sathishmahi — its a ML,in this library cover almost every ML process.this library mostly used for biginner
• joeutil — ADP Utils
• kolibri-ml — Deep Learning and more NLP toolkit
• kururu — Data Science
• lohrasb — This versatile tool streamlines hyperparameter optimization in machine learning workflows.It supports a wide range of search methods, from GridSearchCV and RandomizedSearchCVto advanced techniques like OptunaSearchCV, Ray Tune, and Scikit-Learn Tune.Designed to enhance model performance and efficiency, it's suitable for tasks of any scale.
• lucifer-ml — Automated ML by d4rk-lucif3r
• machine-learning-evaluation — A library for evaluating machine learning models.
• mAdvisor — An automated AI/ML solution from Marlabs
• mallu — Package for easier Machine Learning Workflow.
• mgoelAuto — Template python package
• miso2 — Python scripts for training CNNs for particle classification
• ml-helper — Helpers to speed up and structure machine learning projects
• ml2sql — Automated interpretable ML tool with SQL version of model
• MLOne — A Python package with which users can just drop their dataset and download the best ML model for their dataset
• mltlk — Toolkit for making machine learning easier
• modeling-tool — the extension of sklearn to help the your modeling code becomes more concise with common useful tool for modeling
• mustafapy — GridSearchCV hyperparameters generation
• nestedcvtraining — Perform Nested Cross Validation for model training
• NeuraFlow — Pacote para redes neurais e aprendizado de máquina
• neurojit — A Python package for calculating the commit understandability features of Java projects.
• nlp-project — A package for predicting buy and sell signals
• numeritos — Librería para Data Scientists
• OnePiecePredictor — Hyper Paramter Tuning and Models performance comparison
• opencortex — Software to stream EEG data, perform preprocessing, and train machine learning models to build real-time BCI applications.
• optialgo — OptiAlgo menyediakan solusi cepat dan andal untuk mencari algoritma terbaik bagi pengguna, serta memberikan fleksibilitas dalam menangani berbagai masalah data.
• osman — A package which lets users oversample class imbalanced(binary) data by Deep Generative Models. It offers two APIS. They are : variational auto encoder and WGAN-GP.
• pardon — The Data Transformation and Machine Learning Accelerator
• phishing-detection-py — A Python library for phishing detection using machine learning models.
• picklebase — a Python Package
• picklepie — a Python Package
• pneuro — Python API for Automated ML
• polar — Data Science Library
• Potosnail — improves ML workflow
• prepup-linux — Prepup is a free, open-source package for data preprocessing in terminal
• prophetdicebot — ProphetDice Functions
• pychamp — Data Science Tools
• pygrnd — A python library for quantum algorithms and software
• python-allib — A typed Active Learning Library
• pytorch-vision-classifier — This library is to help you train and evaluate PyTorch classification model easily and quickly
• racoons — A package for descriptive analysis of radiological data.
• raise-utils — RAISE lab package
• relionai — Comprehensive ML Testing directly into your stack with just a few lines of code
• scalarpy — Welcome to ScalarPy!
• sctreeshap — sctreeshap: a cluster tree data structure, and for shap analysis
• SIDISH — SIDISH package 1.0.0
• silk-ml — Simple Intelligent Learning Kit (SILK) for Machine learning
• Simba-UW-no-tf — Toolkit for computer classification of complex social behaviors in experimental animals
• Simba-UW-tf — Toolkit for computer classification of complex social behaviors in experimental animals