Pinterest

Today
Watch
Shop
Explore
Explore
Education
Subjects
Math Resources

Principal component analysis

Discover Pinterest’s best ideas and inspiration for Principal component analysis. Get inspired and try out new things.
161 people searched this
·
Last updated 4d
Principal Component Methods in R: Practical Guide - Articles - STHDA Data Science Statistics, Visitor Guest Book, Quantitative And Qualitative, Principal Component Analysis, Plotting Points, Data Science Learning, Computer Security, Data Mining, Data Analysis
Data Science Statistics
Visitor Guest Book
Quantitative And Qualitative
Principal Component Analysis
Plotting Points
Data Science Learning
Computer Security
Data Mining
Data Analysis

Principal Component Methods in R: Practical Guide - Articles

Principal component methods are used to summarize and visualize the information contained in a large multivariate data sets. Here, we provide practical examples and course videos to compute and interpret principal component methods (PCA, CA, MCA, MFA, etc) using R software. The following figure illustrates the type of analysis to be performed depending on the type of variables contained in the data set. The Book: Practical Guide to Principal Component Methods in R…

32
The Fundamental Difference Between Principal Component Analysis and Factor Analysis Factor Analysis, Data Science Statistics, Statistics Notes, Principal Component Analysis, Research Methods, Book Writing Tips, Biotechnology, Deep Learning, Data Analysis
Factor Analysis
Data Science Statistics
Statistics Notes
Principal Component Analysis
Research Methods
Book Writing Tips
Biotechnology
Deep Learning
Data Analysis

The Fundamental Difference Between Principal Component Analysis and Factor Analysis

Principal Component Analysis and Factor Analysis are similar in many ways. They appear to be varieties of the same analysis rather than two different methods. Yet there is a fundamental difference between them that has huge effects on how to use them.

87
Principal Component Analysis, Supervised Learning, Data Visualization Tools, Data Map, Data Visualisation, Standard Deviation, Gene Expression, Learning Methods, Learning Techniques
Principal Component Analysis
Supervised Learning
Data Visualization Tools
Data Map
Data Visualisation
Standard Deviation
Gene Expression
Learning Methods
Learning Techniques

Introduction to Principal Component Analysis - DataScienceCentral.com

This formula-free summary provides a short overview about how PCA (principal component analysis) works for dimension reduction, that is, to select k features (also called variables) among a larger set of n features, with k much smaller than n. This smaller set of k features built with PCA is the best subset of k features,… Read More »Introduction to Principal Component Analysis

23
Principal component analysis and more

Explore related boards

手机版prototype

,
97 Pins
,
2y

CS

,
382 Pins
,
1w

machine learning

,
40 Pins
,
1mo

Data 👩‍💻

,
315 Pins
,
4d

Data science learning

,
430 Pins
,
2mo

Related interests

Competitive Analysis
Fundamental Analysis
Impulsive Ideas
Personal Swot Analysis Example
Stakeholder Analysis