principal component analysis

Principal Component Analysis (PCA)

Towards Data Science

The principal component analysis (PCA) involves rotating a cloud of data points in Euclidean space such that the variance is maximal along the first axis, the so-called first principal component. The…...

Principal Component Analysis- A Brief Understanding

Analytics Vidhya

Principal Component Analysis (PCA) is an unsupervised technique for reducing the dimension of the data. The idea behind PCA is to seek the most accurate data representation in a lower-dimensional…

Principal Component Analysis explained

Towards Data Science

Principal Components Analysis (PCA) is one of the most famous algorithms in Machine Learning (ML), it aims to reduce the dimensionality of your data or to perform unsupervised clustering. PCA is…

Kaggle Learn Courses

Introduction In the previous lesson we looked at our first model-based method for feature engineering: clustering. In this lesson we look at our next: principal component analysis (PCA). Just like cl...

In-depth Principal Component Analysis

Analytics Vidhya

The Principal Component Analysis or PCA is an unsupervised learning method and is used for dimensionality reduction. In this blog, we will understand it in-depth and learn how to use it. Machine…

The Essence of Principal Component Analysis (PCA)

Towards Data Science

PCA is the simplest of the true eigenvector-based multivariate analyses. It is most commonly used as a dimensionality-reduction technique, reducing the dimensionality of large data-sets while still…

Tidying up with PCA: An Introduction to Principal Components Analysis

Towards Data Science

Principal component analysis (PCA) is a technique for dimensionality reduction, which is the process of reducing the number of predictor variables in a dataset. More specifically, PCA is an…

Like Principal Components Analysis?

Towards AI

Introduction Principal Component Analysis (PCA) is a dimensionality reduction technique that projects the input variables that describe a set of objects into linear combinations of these variables to ...

What is Principal Component Analysis

Analytics Vidhya

Ever had a bunch of features while training a model but couldn’t figure out which ones are best suited? You might have come across principal component analysis, PCA for short, at that juncture. In a…

Introduction to Principal Component Analysis (PCA)

OpenCV Tutorial

In this tutorial you will learn how to: What is PCA? Principal Component Analysis (PCA) is a statistical procedure that extracts the most important features of a dataset. Consider that you have a set ...

Understanding Principle Component Analysis(PCA) step by step.

Analytics Vidhya

Principal component analysis (PCA) is a statistical procedure that is used to reduce the dimensionality. It uses an orthogonal transformation to convert a set of observations of possibly correlated…

The Magic of Principal Component Analysis through Image Compression

Towards Data Science

Principal Component Analysis or PCA is a dimensionality reduction technique for data sets with many continuous (numeric) features or dimensions. It uses linear algebra to determine the most important…...