survival-analysis 开源项目推荐（1,546 个）

CamDavidsonPilon /lifelines

Survival analysis in Python

mlr-org /mlr

Machine Learning in R

sebp /scikit-survival

Survival analysis built on top of scikit-learn

havakv /pycox

使用 PyTorch 进行生存分析

MatthewReid854 /reliability

Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/

square /pysurvival

Open source package for Survival Analysis modeling

autonlab /auton-survival

Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

loft-br /xgboost-survival-embeddings

Improving XGBoost survival analysis with embeddings and debiased estimators

sktime /skpro

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

archd3sai /Customer-Survival-Analysis-and-Churn-Prediction

In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.

robi56 /Survival-Analysis-using-Deep-Learning

本仓库包含莫登·贝斯统计和基于深度学习的研究文章，以及用于生存分析的软件

Novartis /torchsurv

Deep survival analysis made easy

m-clark /Miscellaneous-R-Code

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.

vanderschaarlab /autoprognosis

A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.

gpstuff-dev /gpstuff

GPstuff - Gaussian process models for Bayesian analysis

kokikwbt /predictive-maintenance

Datasets for Predictive Maintenance

mlr-org /mlr3proba

Probabilistic Learning for mlr3

rk2900 /DRSA

Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper and a benchmark for several (Python) implemented survival analysis methods.

KatherLab /STAMP

Solid Tumor Associative Modeling in Pathology

tylermorganwall /skpr

Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.