regularization

Vocabulary Word

Definition

'Regularization' is a technique used in machine learning and statistics to prevent overfitting. It helps models to not pay too much attention to the noise in the data and makes them more general and practical to use.

Examples in Different Contexts

In business analytics, 'regularization' can optimize model performance for predictive analytics. A business analyst might assert, 'Applying regularization techniques improves our predictive models, allowing for more reliable business forecasts and better strategic planning.'

Practice Scenarios

Academics

Scenario:

Our current model for analyzing climate change trends is not generalising well. We need to enhance its reliability.

Response:

Correct. Introducing regularization could help prevent the model from overfitting and ensure it generalizes well across different datasets.

Business

Scenario:

Our current model for predicting quarterly revenue is overfitting the historical data and needs refining.

Response:

I agree. Perhaps we should apply a Lasso regularization to our model to simplify it and improve predictions.