dimensionality-reduction

Vocabulary Word

Definition

'Dimensionality reduction' is about simplifying data without losing important information. It's like creating a summary of a book, where you keep the main points but leave out the details.

Examples in Different Contexts

In analytics, 'dimensionality reduction' is used to simplify data visualization and interpretation by reducing the number of dimensions without significant loss of information. An analyst might state, 'Applying dimensionality reduction techniques has enabled us to identify key trends more clearly in complex datasets.'

Practice Scenarios

Academics

Scenario:

This large dataset has so many variables. We need to clearer picture for our research study.

Response:

Applying dimensionality reduction on our dataset can better highlight the most relevant research factors.

Innovation

Scenario:

We have access to a broad spectrum of patient data. However, it is crucial to isolate the most relevant health indicators.

Response:

Dimensionality reduction could help us identify the best health indicators from this large dataset.