GitHub / emaynard10 / Credit_Risk_Analysis
Using supervised machine learning to predict credit risk. Trying oversampling, under sampling, combination sampling and ensemble learning to find the model with the best fit
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PURL: pkg:github/emaynard10/Credit_Risk_Analysis
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License: None
Language: Jupyter Notebook
Size: 20.7 MB
Dependencies parsed at: Pending
Created at: almost 3 years ago
Updated at: almost 3 years ago
Pushed at: almost 3 years ago
Last synced at: over 2 years ago
Topics: clustering-algorithm, confusion-matrix, decision-trees, ensemble-learning, gradientboostedtrees, labelencoder, logistic-regression, machine-learning, oversampling, pandas, precision-recall, python, randomforestclassifier, smoteen, standardscaler, supervised-machine-learning