README.md

In economistgame/OptimClassifier: Create the Best Train for Classification Models

OptimClassifier

OptimClassifier provides a set of tools for creating models, selecting the best parameters combination for a model, and select the best threshold for your binary classification. The package contains tools for:

• Linear Model (LM)
• Generalized Linear Model (GLM)
• Linear Mixed Model (LMM)
• Classification And Regression Tree (CART)
• Discriminant Analysis (DA)
• Neural Networks (NN)
• Support Vector Machines (SVM)

as well as others that will be implemented in the future.

Installation

Install this package from CRAN (stable version):

install.packages("OptimClassifier")

Install this package from Github (development version):

For this, you can choose different packages such as:

With devtools

library(devtools)
install_github("economistgame/OptimClassifier")

With remotes

library(remotes)
install_github("economistgame/OptimClassifier")

A simple example

This is a basic example which shows you how to solve a common credit scoring problem with this package:

## Load a Dataset
data(AustralianCredit)

## Create the model
creditscoring <- Optim.GLM(Y~., AustralianCredit, p = 0.7, seed=2018)

#See a ranking of the models tested
print(creditscoring)

#Access to summary of the best model
summary(creditscoring)

#Do not sure of like the best model??, you can access to the all model, for example the 2nd model
summary(creditscoring,2)

Bugs and feature requests

If you find problems with the package, or there's anything that it doesn't do which you think it should, please submit them to https://github.com/economistgame/OptimClassifier/issues. In particular, let me know about optimizers and formats which you'd like supported, or if you have a workflow which might make sense for inclusion as a default convenience function.

economistgame/OptimClassifier documentation built on Jan. 25, 2022, 12:22 p.m.