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Built fraud detection classifiers using gaussian naive bayes and decision tress to identify POIs (persons of interests) and applied machine learning techniques such as features selection, precision and recall, and stochastic gradient descent for optimization in Python.

  • Updated Apr 14, 2017
  • Python

The proposed algorithm is successful in elimination of 108 rows from Pima Diabetes Dataset by skewness range of Normal distribution curve. To check the efficacy of the algorithm, it is compared with four techniques- Local Outlier Factor, Mahalanobis Distance, Multivariate Normal Distribution (N Dimensional) and DBSCAN.

  • Updated Jun 13, 2024
  • Jupyter Notebook

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