Python PyCaret Getting Started with PyCaret 2.0














































Python PyCaret Getting Started with PyCaret 2.0



 

Getting Started with PyCaret 2.0



The first step of any machine learning experiment in PyCaret is to set up an environment by importing the relevant module and initialize the setup function by passing dataframe and name of the target variable. 

See example code:

# Import module
from pycaret.classification import *

# Initialize setup (when using Notebook environment)
clf1 = setup(data, target = 'target-variable')

# Initialize setup (outside of Notebook environment)
clf1 = setup(data, target = 'target-variable', html = False)

# Initialize setup (When using remote execution such as Kaggle / GitHub actions / CI-CD pipelines)
clf1 = setup(data, target = 'target-variable', html = False, silent = True)

Sample Output:

Figure

Output is truncated

 

All the preprocessing transformations are applied within setup function. PyCaret provides over 20 different pre-processing transformation that can be defined within setup function. Click here to learn more about PyCaret%u2019s preprocessing abilities.

Figure

https://www.pycaret.org/preprocessing
In the next article, we'll learn to compare different models using PyCaret 2.0.
Until then, HAPPY PYTHONING....!!


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