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

Fuzzy Logic

Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…

Feature Extraction

Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…

One-Shot Learning

One-Shot learning is an AI approach that enables models to learn from only one or a few examples. This approach is advantageous in tasks…

Supervised Learning

Supervised Learning is a Machine Learning approach where models are trained using labelled data, with both input and output pairs. By learning from the…
Back to Glossary