autoprognosis
scikit-survival
| autoprognosis | scikit-survival | |
|---|---|---|
| 2 | 1 | |
| 89 | 1,072 | |
| - | - | |
| 5.0 | 8.9 | |
| 7 months ago | about 23 hours ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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.
autoprognosis
- AutoPrognosis: Automating the model selection for clinical prognosis
-
[P] AutoPrognosis - A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
Code: https://github.com/vanderschaarlab/autoprognosis
scikit-survival
What are some alternatives?
hyperimpute - A framework for prototyping and benchmarking imputation methods
pycox - Survival analysis with PyTorch
auton-survival - Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
xgboost-survival-embeddings - Improving XGBoost survival analysis with embeddings and debiased estimators
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies