README.md

In modelplotr: Plots to Evaluate the Business Performance of Predictive Models

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.

modelplotr documentation built on Oct. 23, 2020, 8:20 p.m.