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The objective of my experiment is to analyze the performance of Random Forest, Naive Bayes, Logistic Regression, and K-nearest neighbors machine learning models for evaluation of the utility of synthesized data for fraud detection.

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fraud-detection fraudulent-transactions imbalanced-classification imbalanced-data machine-learning synthetic-data

evaluation-the-quality-of-synthetic-data-set-for-fraud-detection's Introduction

Hi there ๐Ÿ‘‹

I am 4th year Bachelor's student at METU in Turkey.

As a senior mathematics student, I am excited to bring my strong analytical and problem-solving skills to the field of Machine Learning. With a solid foundation in mathematics, especially in combinatorics, and programming experience in Python, SQL, and C#, I am eager to tackle challenges in the field of generative AI and computational neuroscience.

Programming Skills

python mysql c csharp matlab

Frameworks

pandas scikit_learn tensorflow

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