Principal Component Analysis

• Uses:

– Data Visualization

– Data Reduction

– Data Classification

– Trend Analysis

– Factor Analysis

– Noise Reduction

• Examples:

– How many unique “sub-sets” are in

the sample?

– How are they similar / different?

– What are the underlying factors that

influence the samples?

– Which time / temporal trends are

(anti)correlated?

– Which measurements are needed to

differentiate?

– How to best present what is

“interesting”?

– Which “sub-set” does this new sample

rightfully belong?-Principal Component Analysis

•　Uses:

– Data Visualization

– Data Reduction

– Data Classification

– Trend Analysis

– Factor Analysis

– Noise Reduction

•　Examples:

– How many unique “sub-sets” are in

the sample?

– How are they similar/different?

– What are the underlying factors that

influence the samples?

– Which time/temporal trends are

(anti)correlated?

– Which measurements are needed to

differentiate?

– How to best present what is

“interesting”?

– Which “sub-set” does this new sample

rightfully belong?