Which of the following techniques can help in reducing the dimensionality of continuous features? a) t-SNE b) One-hot encoding c) target encoding d) frequency encoding

Understand the Problem

The question is asking about techniques that can reduce the dimensionality of continuous features. It provides four options, out of which we need to identify the appropriate techniques for dimensionality reduction.

More Information

t-SNE (t-Distributed Stochastic Neighbor Embedding) is a technique for dimensionality reduction that is particularly good at visualizing high-dimensional datasets by reducing them to two or three dimensions. It's widely used in applications like clustering and visualization of high-dimensional data.

Sources

• Top 12 Dimensionality Reduction Techniques - Analytics Vidhya - analyticsvidhya.com
• Feature Engineering tips and tricks - Kaggle - kaggle.com