model-generalization

Vocabulary Word

Definition

'Model-generalization' is using a simple model to explain complex cases. It's like using a model car to understand how real cars work.

Examples in Different Contexts

In data science projects, improving 'model generalization' means ensuring the model can be applied broadly. A data scientist might explain, 'By using a diverse training set, we aim to improve our model's generalization to work well across multiple scenarios.'

Practice Scenarios

Business

Scenario:

Examining successful business models, we're interested in creating a universal approach for different markets.

Response:

Model-generalization can certainly help us extract key lessons from successful cases and apply them to different markets.

Tech

Scenario:

Assessing our machine-learning algorithm, we want it to perform as effectively with new data as on the trained data.

Response:

It sounds like we need to improve the model-generalization capabilities of our machine learning algorithm.