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

Natural Language Generation is an AI technique that converts structured data into human-like text. NLG systems use Machine Learning algorithms to understand the data…
Bias in AI refers to systematic errors or prejudices that can occur within AI systems due to biased training data, faulty algorithms, or human…
Evolutionary Computation is a branch of AI inspired by biological evolution and natural selection. It involves using algorithms to mimic evolutionary processes such as…
Decision Trees are Machine Learning models that use a branching structure to make decisions or predictions. By determining the most important features and creating…