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Simplifying Machine Learning with PyCaret in Python

Solution Review: Train Random Forest Model

Explore the process of training a random forest model for regression using PyCaret. Learn how to load data, initialize the environment for model building, and create a random forest model step-by-step to enhance your machine learning skills.

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Solution

Python 3.5
# Load the automobile dataset to a variable named `data`
 data = get_data('automobile')
# Initialize PyCaret environment and assign result to a variable named `reg1`
 reg1 = setup(data, target = 'price', silent = True)
# Create a Random Forest model and assign it to a variable named `model`.
 model = create_model('rf')

Explanation

  • Line 3: We load the automobile dataset into the data
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