'OneHotEncoder' object has no attribute 'get'

The error message "'OneHotEncoder' object has no attribute 'get'" typically occurs when you try to call the 'get' method on an instance of the OneHotEncoder class in scikit-learn.

The OneHotEncoder class in scikit-learn does not have a 'get' method. Instead, you should use the 'transform' method to convert your input data to the one-hot encoded representation.

Here's an example of how to use the OneHotEncoder class to one-hot encode a categorical variable:

from sklearn.preprocessing import OneHotEncoder
import numpy as np

# create some categorical data
data = np.array([['red', 'small'], ['blue', 'large'], ['green', 'medium']])

# create an instance of the OneHotEncoder class
enc = OneHotEncoder()

# fit the encoder to the data and transform the data to one-hot encoding
one_hot_data = enc.fit_transform(data).toarray()

print(one_hot_data)

In this example, the 'fit_transform' method of the OneHotEncoder class is used to fit the encoder to the data and transform the data to a one-hot encoded representation. The resulting one-hot encoded data is then printed to the console.