How to implement PageRank Algorithm

This is an article on a fast Julius interface that I used to quickly create a credit card fraud detection list using the PageRank algorithm.

The detection process can easily find out if a user credit card transaction is secure, or any anomalies or activity done by an unauthenticated person.

The left plot shows the distribution of transaction amounts, which appears to be highly skewed towards lower values, indicating that most transactions involve small amounts of money.
The right plot illustrates the distribution of transaction times, measured in seconds from the first transaction in the dataset. This distribution seems fairly uniform, suggesting transactions occur at a consistent rate over time.

Here is the scatter plot of transaction amount versus transaction time:


Very cool, I didn’t know you could use Julius to detect fraud patterns in users! We can see a few outliers in the dataset, but what would you see if you detected fraud here? Would there be a clustering of outliers in a specific area?

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Yes we can further find conclusion on detection but in starting onwards it’s just a basic thing to describe
What about tshirt or sweatshirt when it will be provided


Thank you for further clarifying this. It should be sent out soon, just keep an eye out for it in the mail :slight_smile: