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sushantdhumak / Credit-Card-Fraud-Detection

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Demonstrates the use of ML for Anomaly Detection for Credit Card Transactions: Identifying Fraudulent Activity using Imbalanced Data

exploratory-data-analysis data-visualization logistic-regression outlier-detection decision-tree-classifier imbalanced-data outlier-removal svc random-forest-classifier roc-auc gridsearchcv precision-recall-curve knn-classifier correlation-analysis anamoly-detection under-sampling roc-auc-curve data-scaling near-miss
  • Updated Jan 7, 2025
  • Jupyter Notebook

DanniRodrJ / milling-machine_failure-prediction

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Machine Learning aplicado al mantenimiento predictivo. Se realizaron 2 modelos: 1 por medio de clasificación binaria que predice si una máquina fresadora estará en riesgo de fallar o no, y el 2 modelo a través de clasificación multiclase que predecirá el modo de falla

python sklearn logistic-regression decision-tree-classifier binary-classification svm-classifier multilabel-classification gridsearchcv randomsearch optuna smotetomek pickle-file near-miss catboost-classifier
  • Updated Nov 8, 2023

msikorski93 / Credit-Card-Fraud-Detection

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A binary classification task performed with machine learning in Python. The dataset's target distribution is heavily imbalanced. The model performance was evaluated with F1 scores.

tensorflow naive-bayes credit-card-fraud logistic-regression k-means binary-classification f1-score resampling-methods k-nearest-neighbors adasyn random-undersampling light-gradient-boosting-machine near-miss smote-enn class-imbalance-handling random-oversampling balanced-bagging
  • Updated Dec 2, 2024
  • Jupyter Notebook

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