vintage_function

A data.frame contained id, occur_time, mob, status ...

The name of ID of observations or key variable of data. Default is NULL.

obs_id

The name of the variable that represents the time at which each observation takes place.

occur_time

Period of event to analysiss. Default is "monthly"

period

status

The name of variable representing amount. Default is NULL.

amount

Output: amount (amt) or count (cnt)

by_out

The earliest occurrence time of observations.

start_date

The latest occurrence time of observations.

end_date

dead_status

This function is not intended to be used by end user.


Provides a toolkit for building predictive models in one integrated offering. Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyperparameters, data mining and visualization, model evaluation, strategy analysis etc. 'creditmodel' is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster.
The references including:
1.Anderson, R. (2007). The credit scoring toolkit: Theory and practice for retail credit risk management and decision automation.
2.Find, S. (2012, ISBN13: 9780230347762). Credit scoring, response modelling and insurance rating:A practical guide to forecasting consumer behaviour.

vintage_function: vintage_function `vintage_function` is for vintage analysis.

Description

Usage

Arguments