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Train a Random Forest model to predict credit card fraudulent transactions
pip install tid-credit-card-fraud-prediction
PyPI declares 168 unique dependency rules for this release. Environment markers are shown when supplied by the project.
==3.6.2==0.1.3==21.3.0==21.2.0==1.2.3==2.2.1==22.2.0==0.1.58==0.2.0==4.11.1==22.12.0==5.0.1==2.4.3==5.3.0==2.6.0==2022.12.7==1.15.1==5.1.0The compact report shows 18 of 168 declarations. The interactive dependency graph loads the complete metadata.
tid-credit-card-fraud-prediction publishes 1 wheel and 1 source archive for version 0.0.4. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.6, 3.7, 3.8, 3.9.
PyPI lists 4 releases with files. The first dated release is ; 4 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .