GitHub topics: explain-classifiers
ModelOriented/fairmodels
Flexible tool for bias detection, visualization, and mitigation
Language: R - Size: 142 MB - Last synced at: 8 days ago - Pushed at: 4 months ago - Stars: 86 - Forks: 16
edahelsinki/pyslise
Robust regression algorithm that can be used for explaining black box models (Python implementation)
Language: Python - Size: 3.55 MB - Last synced at: 25 days ago - Pushed at: about 1 year ago - Stars: 6 - Forks: 1
edahelsinki/slise
Robust regression algorithm that can be used for explaining black box models (R implementation)
Language: R - Size: 3.72 MB - Last synced at: 14 days ago - Pushed at: almost 2 years ago - Stars: 5 - Forks: 1
namsor/Java-Naive-Bayes-Classifier-JNBC
A scalable, explainable Java Naive Bayes Classifier that works either in memory or on persistent fast key-value store (MapDB, RocksDB or LevelDB)
Language: Java - Size: 1.25 MB - Last synced at: 2 months ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 4
p-disha/Data-Mining-on-Newsgroup-data
Designed a Machine Learning model which takes newsgroup dataset and performs binary classification to predict if a given document has Atheistic or Christian sentiment. Used LIME library and PySpark. Performed feature selection to improve classifier’s performance.
Language: Python - Size: 15.6 KB - Last synced at: about 2 months ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0
