Comparing frequency & recency

Now that you've created frequency and recency features, let's compare them between the legitimate transactions and the fraudulent ones. The dataset transfers contains 222 transactions from 4 accounts. The frequency features freq_channel and freq_auth, and the recency features rec_channel and rec_auth have been added as columns to the dataset.

This exercise is part of the course

Fraud Detection in R

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Exercise instructions

Have a look at dataset transfers in the console using functions like head and str.
Get a summary of the frequency and recency channels for legitimate transactions.
Get a summary of the frequency and recency channels for fraudulent transactions.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

library(dplyr)

# Statistics of frequency & recency features of legitimate transactions:
summary(transfers %>% filter(___) %>% select(___, ___, ___, ___))

# Statistics of frequency & recency features of fraudulent transactions:
summary(transfers %>% filter(___) %>% select(___, ___, ___, ___))

Edit and Run Code