Wonderful Library. It enables you to evaluate 42 models in one stroke  for a given data set. Let us have the same data ‘Student Performance’ obtained from Kaggle

Load libraries and read data

 

Separate the features and the target

 

 

Split the data into trainset and testset

 

Load  LazyRegressor and LazyClassifier lib

 

this one makes you lazy, the object function provides you models and predictions in one stroke. The arguments are the train-sets and test-sets of both features and target

 

predictions

 

  1. cyan colored model is the best model which has the highest  R-squared rating
  2. lightred colored model is the worst model which has the lowest R-Squared rating