modelplotr: Plots to evaluate the business value of predictive models
The modelplotr package makes it easy to create a number of valuable
evaluation plots to assess the business value of a predictive model.
Using these plots, it can be shown how implementation of the model will
impact business targets like response or return on investment of a
campaign.
Plots available with modelplotr:
- cumulative gains
- cumulative lift
- response
- cumulative response
- costs & revenues
- profit
- return on investment
Some benefits of using modelplotr:
- easy to explain plots to discuss your model with business
- easy to use on top of predictive models built with caret, mlr,
h2o, keras or otherwise (with or without r)
- supports both binary and multinomial targets
- provides four plotting scopes:
- comparing models
- comparing datasets
- comparing multiclass target classes
- no comparison (single line)
- plot annotation: highlighting specific values and adding
explanatory text to guide interpretation
- plot customization: all textual elements, line colors
- save plot to file on disk
Installation
You can install modelplotr
from
GitHub with:
devtools::install_github("modelplot/modelplotr")
See this blog for further details and examples of using the package.