Archive | Ensemble Learning

How to Develop Super Learner Ensembles in Python

How to Develop Super Learner Ensembles in Python

Selecting a machine learning algorithm for a predictive modeling problem involves evaluating many different models and model configurations using k-fold cross-validation. The super learner is an ensemble machine learning algorithm that combines all of the models and model configurations that you might investigate for a predictive modeling problem and uses them to make a prediction […]

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How to Use Out-of-Fold Predictions in Machine Learning

How to Use Out-of-Fold Predictions in Machine Learning

Machine learning algorithms are typically evaluated using resampling techniques such as k-fold cross-validation. During the k-fold cross-validation process, predictions are made on test sets comprised of data not used to train the model. These predictions are referred to as out-of-fold predictions, a type of out-of-sample predictions. Out-of-fold predictions play an important role in machine learning […]

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