Choosing a good value for PCA Dimensionality Reduction

A quick code to reduce dimensionality of data

Gustavo Santos
Towards Data Science
4 min readOct 25, 2022

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Photo by Mihály Köles on Unsplash

Introduction

If you ever faced a dataset with, let’s say, 100 features, you probably thought about reducing the number of dimensions of it.

First, because it is really difficult for us to create compelling visualizations having that many…

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Data Scientist. I extract insights from data to help people and companies to make better and data driven decisions. | In: https://www.linkedin.com/in/gurezende/