The content regarding early in the day applications for financing in the home Borrowing out of members who possess loans on application studies
I fool around with you to-sizzling hot security and then have_dummies to your categorical details on the application urgent link analysis. On nan-viewpoints, i use Ycimpute library and you will predict nan philosophy during the mathematical variables . Having outliers analysis, we use Local Outlier Basis (LOF) towards app analysis. LOF detects and you will surpress outliers research.
For each most recent mortgage on application data may have multiple past funds. Per past app provides you to definitely row and that’s identified by the brand new feature SK_ID_PREV.
I’ve one another drift and you will categorical details. I apply score_dummies to have categorical parameters and you can aggregate to (imply, minute, maximum, matter, and you will sum) for drift details.
The info out of payment records for earlier financing yourself Credit. Discover you to definitely row for every generated percentage and another row for every single overlooked payment.
With respect to the shed really worth analyses, destroyed values are so brief. So we don’t have to need one step to own lost viewpoints. I’ve both drift and you may categorical variables. We use get_dummies to own categorical details and you will aggregate to (mean, min, max, number, and contribution) having drift variables.
This info includes month-to-month harmony pictures out of previous handmade cards one to the brand new applicant obtained from your home Borrowing
They consists of monthly analysis about the earlier credits from inside the Agency research. Read more “The content regarding early in the day applications for financing in the home Borrowing out of members who possess loans on application studies”
