Principal Component Analysis (PCA) is a powerful technique used for dimensionality reduction, which helps in simplifying high-dimensional data while retaining most of the variance. Visualizing PCA results can provide insights into the structure and relationships within the data.

Visualizing PCA with Plotly

Plotly is a popular library for creating interactive visualizations in Python. It can be used to visualize PCA results effectively. Here's how you can visualize PCA using Plotly:

Scatter Plot Matrix

A scatter plot matrix can be used to visualize the relationships between different features in the dataset. This can help in understanding how different features correlate with each other.