Updated 9 months ago
shap
A game theoretic approach to explain the output of any machine learning model.
Updated 9 months ago
asaca-automatic-speech-analysis-for-cognitive-assessment
Transform speech into cognitive assessments with ASACA. Achieve accurate predictions and low error rates using our end-to-end toolkit. 🚀🔧
Updated 9 months ago
https://github.com/astrazeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Updated 9 months ago
modeling-uncertainty-local-explainability
Local explanations with uncertainty 💐!
Updated 9 months ago
survex
Explainable Machine Learning in Survival Analysis
biostatistics
brier-scores
censored-data
cox-model
cox-regression
explainable-ai
explainable-machine-learning
explainable-ml
explanatory-model-analysis
interpretable-machine-learning
interpretable-ml
machine-learning
probabilistic-machine-learning
r
r-package
shap
survival-analysis
time-to-event
variable-importance
xai
Updated 9 months ago
asaca-automatic-speech-analysis-for-cognitive-assessment
The automatic system that can extract PRAAT-like speech features from raw speech wav files, and also can get low WER (<10) high quality transcriptions at the same time.
Updated 9 months ago
https://github.com/cyriljl/apyxl
apyxl simplifies non-linear regressions/classifications and model explainability for all users