Search for a command to run...
Series
Following my credit card fraud detection project from absolute zero. Each post is one day of the build ; setup, data exploration, model training, and everything that breaks along the way. Written for anyone else starting from scratch.
I'm building a credit card fraud detection project from scratch. But before I could touch any data, I had a smaller problem: how do I actually get a Kaggle dataset into my notebook? My old method was
Day 1 was setup. Day 2 was the first time I actually looked at the data and the numbers immediately broke my assumptions. Here's what the credit card fraud dataset told me. The problem it solves I had
Why stratify=y is the most important argument in my train/test split.
Day 3 was splitting. Day 4 was my first actual model : a baseline logistic regression. The model trained fine. The AUC looked great. But the confusion matrix and classification report are what finally
My recall jumped from 59% to 81%. My precision dropped from 79% to 57%.
The chart doesn't decide for you. I had to.
