cluster-centroid-undersampling

There are 0 repository under cluster-centroid-undersampling topic.

Kenner82 / Credit_Risk_Analysis
Testing 6 different machine learning models to determine which is best at predicting credit risk.
ada-boost-classifier balanced-random-forest cluster-centroid-undersampling ensemble-learning naive-random-oversampler oversampling-algorithms smote-oversampler smoteenn-combination combination-sampling-algorithms undersampling-algorithms pandas python supervised-machine-learning
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GR8505 / Credit_Risk
Performed supervised machine learning using oversampling, undersampling and combination sampling techniques to determine credit risk for bank customers.
scikit-learn imblearn ada-boost-classifier random-forest smote cluster-centroid-undersampling
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LJD0 / Credit_Risk_Analysis
Analysis of different machine learning models' performance on predicting credit default
balanced-random-forest cluster-centroid-undersampling easy-ensemble-classifier machine-learning numpy pandas python random-over-sampling smote smoteenn
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Credit_Risk_Analysis
ramya-ramamur / Credit_Risk_Analysis
Determine supervised machine learning model that can accurately predict credit risk using python's sklearn library. Python, Pandas, imbalanced-learn, skikit-learn
random-forest ensemble-learning smote-oversampler smoteenn-combination easyensembleclassifier cluster-centroid-undersampling naive-random-oversampler balanced-random-forest python scikit-learn imbalanced-learning
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Wall-E28 / credit_risk_analysis
The purpose of this analysis was to create a supervised machine learning model that could accurately predict credit risk using python's sklearn library.
risk random-forest precision accuracy-score recall smote smoteenn cluster-centroid-undersampling naive-random-oversampler ensemble-classifier python sklearn
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inregards2pluto / credit-risk-analysis
Use scikit-learn and imbalanced-learn machine learning libraries to assess credit card risk.
cluster-centroid-undersampling ensemble-model machine-learning naive-random-oversampling smote-oversampling smoteenn-combination-sampling adaboost-classifier balanced-random-forest
Language:Jupyter Notebook