Principal Component Analysis (PCA) and Factor Analysis
What you'll learn
- Understand Principal Component Analysis and Factor Anallysis in crysal clear manner
- Will know how to coduct principal component analysis and factor analysis using SAS / R
- Will understand, how PCA helps in dimensionality reduction
- Will understand the difference and similarity between PCA and factor analysis
- Students will be able to use PCA for variable selection
Requirements
- The course will start with elementary concepts but knowledge of basic statistics will help
- For execution - it will help to know basic SAS or R programming
Description
The course explains one of the important aspect of machine learning - Principal component analysis and factor analysis in a very easy to understand manner. It explains theory as well as demonstrates how to use SAS and R for the purpose.
The course provides entire course content available to download in PDF format, data set and code files. The detail course content is as follows.
- Intuitive Understanding of PCA 2D Case
- what is the variance in the data in different dimensions?
- what is principal component?
- Formal definition of PCs
- Understand the formal definition of PCA
- Properties of Principal Components
- Understanding principal component analysis (PCA) definition using a 3D image
- Properties of Principal Components
- Summarize PCA concepts
- Understand why first eigen value is bigger than second, second is bigger than third and so on
- Data Treatment for conducting PCA
- How to treat ordinal variables?
- How to treat numeric variables?
- Conduct PCA using SAS: Understand
- Correlation Matrix
- Eigen value table
- Scree plot
- How many pricipal components one should keep?
- How is principal components getting derived?
- Conduct PCA using R
- Introduction to Factor Analysis
- Introduction to factor analysis
- Factor analysis vs PCA side by side
- Factor Analysis Using R
- Factor Analysis Using SAS
- Theory for using PCA for Variable Selection
- Demo of using PCA for Variable Selection
Who this course is for:
- Analytics Professionals
- Research Scholars
- Data Scientists
Course content
- Preview01:21
- Preview01:23
- 07:52Intuitive Understanding of PCA 2D Case
- 03:43Formal defintion of PCs
- Preview02:36
- 07:25Properties of Principal Components - part 2
- 07:52Data Treatment for conducting PCA
- 15:11Workshop - conduct principal component analysis using SAS
- 06:24Workshop - conduct principal component analysis using R
Instructor
![Gopal Prasad Malakar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.1 Instructor Rating
- 9,339 Reviews
- 105,142 Students
- 16 Courses
I am a seasoned Analytics professional with 18+ years of professional experience. I have industry experience of impactful and actionable analytics, data science, decision strategy and enterprise wise data strategy.
I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios.
My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting, business intelligence systems like tableau /SAS Visual Analytics, MS access based database application development, Enterprise wide big data framework and streaming analysis.
Please refer to my course for
- SAS / R program details (syntax and options)
- SAS / R output deep dive
- Practical usage in Industrial situation