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Credit Card Fraud Detection Using Spectral Clustering

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SEPTEMBER 16, 2024

Supervised Learning These methods require labeled data to train the model. The model learns to distinguish between normal and abnormal data points. For example, in fraud detection, SVM (support vector machine) can classify transactions as fraudulent or non-fraudulent based on historically labeled data.

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Supervised vs Unsupervised Learning: Key Differences

How to Learn Machine Learning

MARCH 25, 2025

It groups similar data points or identifies outliers without prior guidance. Type of Data Used in Each Approach Supervised learning depends on data that has been organized and labeled. This data preparation process ensures that every example in the dataset has an input and a known output.

Supervised Learning

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Credit Card Fraud Detection Using Spectral Clustering

Supervised vs Unsupervised Learning: Key Differences

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