24 dependents
| Package | Description | Downloads/month |
|---|---|---|
| PiML (Python Interpretable Machine Learning) toolbox for model development & dia... | 9K | |
| Interpretable binning with temporal stability diagnostics for credit risk, PD, a... | 2K | |
| scorecardpipeline封装常用的风控策略分析和评分卡建模相关组件，支持pipeline式端到端评分卡建模、三方数据分析、规则集效果评估、特征有效性分... | 1K | |
| scikit-learn compatible tools for building credit risk acceptance models | 1K | |
| A package for stat and data miner,calculate woe and iv,and plot woe ,plot iv,cal... | 1K | |
| Make Data Scientist life Easier Tool | 1K | |
| High-performance Risk Modeling Toolkit powered by Polars | 1K | |
| General utilities for data science projects | 1K | |
| automl_tools | 617 | |
| Framework for ML and DS: Automating pipelines from training to deployment | 511 | |
| A rigorous Python toolkit for predictive ML — feature analysis, interaction test... | 403 | |
| Unofficial Python implementation of the RACER classification algorithm | 394 | |
| Credit Risk Modeling Library in Python | 392 | |
| ML Model Development Guide - A comprehensive Streamlit application for building,... | 339 | |
| 自定义的风控自动建模工具包 | 307 | |
| Add your description here | 239 | |
| A comprehensive machine learning pipeline toolkit for feature engineering and mo... | 181 | |
| ClusterExplorer: Explaining Black-Box Clustering Results | 157 | |
| scorescanner streamline the exploration and quantification of relationships betw... | 127 | |
| A hybrid approach for improving the effectiveness of the k-nearest neighbor algo... | 118 | |
| A package for analyzing feature interactions in machine learning models | 93 | |
| A comprehensive machine learning pipeline toolkit for feature engineering and mo... | 67 | |
| A comprehensive machine learning pipeline toolkit for feature engineering and mo... | 66 | |
| A comprehensive machine learning pipeline toolkit for feature engineering and mo... | 65 |
