Cross Validation
Type: Concept
As of November 2026, Cross Validation has been mentioned in 2 episodes across 1 podcast, first heard Aug 2025 on Kaggle. Key technique used to validate model performance in the competition.
Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation includes resampling and sample splitting methods that use different portions of the data to test and train a model on different iterations. It is often used in settings where the goal is prediction, and one wants to estimate how accurately a predic
| Mentioned in | 2 episodes on 1 podcast (as of November 2026) |
|---|---|
| First heard | Aug 2025 on Kaggle |
| Field | Machine Learning |
What do podcasts say about Cross Validation?
2 quotes, recorded on Kaggle.
Who talks about Cross Validation on podcasts?
Cross Validation came up; the most recent mention was Aug 2025 on Kaggle.
What is Cross Validation mentioned alongside?
Cross Validation is most often mentioned alongside Leaderboard, XGBoost and LightGBM.
Affiliated with: Leaderboard
Mentioned together: XGBoost, Leaderboard, LightGBM, Ensemble Methods, Augmentation, CatBoost, Feature Engineering, TF-IDF, Post-processing, Feature Selection