auton-survival VS pgmpy

Compare auton-survival vs pgmpy and see what are their differences.

auton-survival

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

pgmpy

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks. (by pgmpy)
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auton-survival pgmpy
1 2
296 2,621
2.0% 0.8%
4.4 8.0
about 1 month ago 6 days ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

auton-survival

Posts with mentions or reviews of auton-survival. We have used some of these posts to build our list of alternatives and similar projects.

pgmpy

Posts with mentions or reviews of pgmpy. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing auton-survival and pgmpy you can also consider the following projects:

keras - Deep Learning for humans [Moved to: https://github.com/keras-team/keras]

causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.

xgboost-survival-embeddings - Improving XGBoost survival analysis with embeddings and debiased estimators

statsmodels - Statsmodels: statistical modeling and econometrics in Python

pycox - Survival analysis with PyTorch

scikit-learn - scikit-learn: machine learning in Python

CausalPy - A Python package for causal inference in quasi-experimental settings

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

rustworkx - A high performance Python graph library implemented in Rust.

pyhf - pure-Python HistFactory implementation with tensors and autodiff

Lottery-Simulation - This program can simulate a number of drawings in the Lottery (6 out of 49). The guesses and the draws are chosen randomly and the user can choose how many right guesses there should be (0-6). Then the program will run through the simulation as many times as it takes to get the exact number of correct guesses the user chose. The user can also choose how many times this should be repeated (the higher the number, the more accurate the result will be). Then the program will automatically calculate the average number of tries it took to get the chosen number of correct guesses and tell the user the chance of getting this certain number of correct guesses.