Practical Data Science: Reducing High Dimensional Data in R
- 4.4
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Brief Introduction
In this R course, we'll see how PCA can reduce a 5000+ variable data set into 10 variables and barely lose accuracy!Description
In this R course, we'll see how PCA can reduce a 5000+ variable data set down to 10 variables and barely lose accuracy! We'll look at different ways of measuring PCA's effectiveness and other ways of reducing wide data sets (those with lots of features/variables). We'll also look at the advantages and disadvantages with different ways of reducing data.
Requirements
- Requirements
- Some understanding and interest in the R programming language
Manuel Amunategui
4.4 Raiting
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Practical Data Science: Reducing High Dimensional Data in R
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In this R course, we'll see how PCA can reduce a 5000+ variable data set into 10 variables and barely lose accuracy!...
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