What is random state in train-test split?
Understand the Problem
The question is asking for an explanation of the term 'random state' specifically in the context of the train-test split process often used in machine learning. It is likely seeking to understand how it affects the division of data into training and testing sets.
Answer
A parameter to initialize the random number generator for reproducible data splits.
The random_state is a parameter used to initialize the random number generator, ensuring that the data splitting process is reproducible.
Answer for screen readers
The random_state is a parameter used to initialize the random number generator, ensuring that the data splitting process is reproducible.
More Information
Using a fixed random_state value ensures that the split between training and testing data remains the same across multiple runs, aiding in consistency and comparability of the model results.
Tips
Common mistakes include not setting the random_state, leading to different splits every time the code is run, which may affect model evaluation consistency.
Sources
- What Is 'random_state' in sklearn.model_selection.train_test_split ... - saturncloud.io
- scikit-learn random state in splitting dataset - python - Stack Overflow - stackoverflow.com
- train_test_split — scikit-learn 1.5.2 documentation - scikit-learn.org
