In this article, we’ll address a common error encountered when using the PyCaret library in Python: AttributeError: ‘SimpleImputer’ object has no attribute ‘_validate_data’. This error typically arises during the data preprocessing phase specifically when PyCaret tries to use the SimpleImputer from the scikit-learn library. We’ll explain the problem in detail show how to reproduce it and provide the different solutions to resolve it.

Problem Statement

When working with the PyCaret we might encounter an AttributeError similar to the following:

This error usually occurs when there is a version mismatch between the PyCaret and its dependencies especially scikit-learn. The SimpleImputer class in recent versions of the scikit-learn includes the _validate_data method which older versions may not have.

Showing the Problem

Here’s an example that reproduces the error:

from pycaret.datasets import get_data
from pycaret.classification import setup
# Load dataset
data = get_data('juice')
# Initialize setup
clf1 = setup(data, target='Purchase')

Running this code might lead to the following error:

AttributeError: 'SimpleImputer' object has no attribute '_validate_data'

Approach to Solving the Problem

To resolve this issue we need to the ensure compatibility between the PyCaret and its dependencies particularly scikit-learn. There are a few approaches to the tackle this problem:

• Updating scikit-learn: Ensure that you are using the compatible version of the scikit-learn.
• Updating PyCaret: Use the latest version of the PyCaret which is likely to be compatible with the latest dependencies.
• Downgrading PyCaret: Use an older version of the PyCaret that is compatible with the current scikit-learn version.
• Creating a Virtual Environment: The Set up a virtual environment with specific versions of the PyCaret and scikit-learn that are known to be compatible.

Different Solutions to Solve the Error

Solution 1: Update scikit-learn

First, try updating scikit-learn to the latest version:

pip install –upgrade scikit-learn

Solution 2: Update PyCaret

Ensure that we have the latest version of PyCaret:

pip install –upgrade pycaret

Solution 3: Downgrade PyCaret

If updating scikit-learn does not resolve the issue we might need to the downgrade PyCaret to a version compatible with the scikit-learn. For example:

pip install pycaret==2.3.5

Solution 4: Create a Virtual Environment

Create a new virtual environment and install compatible versions of the PyCaret and scikit-learn:

python -m venv pycaret_env

source pycaret_env/bin/activate # On Windows use `pycaret_env\Scripts\activate`

pip install pycaret==2.3.5 scikit-learn==0.24.2

Example Code

Here’s an example showing how to resolve the issue by the downgrading PyCaret:

pip install pycaret==2.3.5 scikit-learn==0.24.2

Now, let’s run the initial example again:

from pycaret.datasets import get_data
from pycaret.classification import setup
# Load dataset
data = get_data('juice')
# Initialize setup
clf1 = setup(data, target='Purchase')

Expected Output

With the compatible versions the setup should initialize without the errors:

Setup Succesfully Completed!

Conclusion

The AttributeError: ‘SimpleImputer’ object has no attribute ‘_validate_data’ in PyCaret can be resolved by the ensuring compatibility between the PyCaret and its dependencies. By updating or downgrading the libraries or by the setting up a controlled virtual environment we can effectively eliminate this error and continue with the data science workflows in PyCaret.