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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.

Jupyter Notebook 40.12% Python 59.88%
machine-learning-algorithms machine-learning evaluation-metric financial-data fraud-detection classifier cross-validation feature-engineering feature-selection

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rsquared2016

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