My Account
Forward Thinking Logo

What is Dimensionality Reduction?

Skill Level:

Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant or redundant features, businesses can simplify data analysis, improve model performance, and reduce computational complexity. Dimensionality Reduction techniques include Principal Component Analysis (PCA) and t-SNE.

Other Definitions

Synthetic Data

Synthetic Data is artificially generated data that mimics real-world data. Synthetic data can be used to train Machine Learning models when real data is…

Clustering

Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or…

Bayesian Networks

Bayesian networks are Probabilistic Graphical Models that represent and evaluate uncertainty and conditional dependencies between variables. Industries such as healthcare and finance use Bayesian…
Back to Glossary