We explore one to-hot security and possess_dummies toward categorical variables toward software studies. For the nan-opinions, i use Ycimpute collection and you may assume nan values within the numerical details . For outliers study, i apply Regional Outlier Factor (LOF) for the software data. LOF finds and you can surpress outliers studies.
For each newest mortgage about app studies might have multiple prior finance. For every prior application features one row and that’s recognized by new ability SK_ID_PREV.
I have each other float and you can categorical parameters. We incorporate get_dummies for categorical parameters and aggregate so you can (indicate, minute, max, count, and elitecashadvance.com/installment-loans-wa/ you may sum) having drift details.
The details from commission history having early in the day finance in the home Credit. There’s that line for every produced payment and one row per missed payment.
With regards to the shed really worth analyses, lost beliefs are incredibly brief. So we don’t have to simply take one step for lost philosophy. You will find each other drift and you may categorical parameters.Okumaya devam et