In choonghyunryu/alookr: Model Classifier for Binary Classification

knitr::opts_chunk$set(collapse = TRUE, comment = "")

Preface

Once the data set is ready for model development, the model is fitted, predicted, and evaluated in the following ways:

• Cleansing the data set
• Split the data into a train set and a test set
• Modeling and Evaluate, Predict
  • Modeling
    • Binary classification modeling
  • Evaluate the model
    • Predict test set using fitted model
    • Calculate the performance metric
    • Plot the ROC curve
    • Tunning the cut-off
  • Predict
    • Predict
    • Predict with cut-off

The alookr package makes these steps fast and easy:

How to perform modeling

Refer to the following website for information on performing modeling, evaluating, and predicting.

• Classification Modeling

choonghyunryu/alookr documentation built on Feb. 28, 2024, 3:04 a.m.