The information and knowledge out of prior apps to own fund yourself Credit off members that have financing throughout the app investigation
We fool around with one to-very hot encoding and also_dummies towards categorical variables for the software research. Into the nan-values, i have fun with Ycimpute collection and expect nan beliefs into the numerical details . Getting outliers research, we use Regional Outlier Factor (LOF) on software investigation. LOF finds and you will surpress outliers study.
Each most recent mortgage regarding the software studies might have several prior fund. Per early in the day application have you to definitely row in fact it is recognized by this new function SK_ID_PREV.
I’ve one another drift and you will categorical parameters. I pertain get_dummies having categorical parameters and you may aggregate to (indicate, minute, max, count, and you will sum) to possess float parameters.
The knowledge off percentage record getting past loans at your home Credit. There’s you to row for each made fee plus one row for each skipped commission.
According https://paydayloanalabama.com/atmore/ to the destroyed worth analyses, missing thinking are small. Therefore we don’t need to take one action for lost opinions. You will find both drift and you will categorical variables. We apply score_dummies to have categorical variables and aggregate so you’re able to (imply, min, max, number, and you will share) for float details.