Screen credit-risk data before building a model.
What it does
Screens credit-risk data for quality and unsuitable features, producing an Excel report of independent cleaning checks.
When to use it
Use when raw credit data needs quality assessment, missing-value analysis, or variable selection before modeling.
How to use it
Give it a credit dataset; it asks for paths, column names, and screening parameters, then saves an Excel cleaning report.
What you provide
- Your files
Latest review
What you need · 8
The execution script uses Python 3.
The pipeline imports pandas for loading and processing tabular data.
The pipeline imports numpy for numerical operations.
The pipeline uses toad for feature binning and information-value calculations.
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