Leave One Out Cross Validation using sklearn in Python

by | Jan 13, 2023 | AI, Machine Learning and Deep Learning, Machine Learning Using Python, Python Scikit-learn

Leave One Out Cross-Validation Using Sklearn

What is Leave One Out Cross Validation, and how does it work?

In our previous article, we discussed what k-fold cross-validation is and how to implement it using sklearn in Python. Leave One Out Cross Validation is a specific variation of k-fold cross-validation where the size of each fold is 1. In other words, in Leave One Out Cross Validation, k number of folds are created where the size of each fold is 1.

So, if there are n records or n rows in the dataset, then n number of folds will be created. In a specific iteration, the model will be trained on (n-1) folds and tested on the left-out fold. In other words, there will be a total of n models. And each model will be tested and evaluated for each record in the dataset.

Leave One Out Cross-Validation

Leave One Out Cross Validation using sklearn in Python

We can use the following Python code to implement Leave One Out Cross Validation using sklearn…

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Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

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